{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import pip\n",
    "#pip.main(['install','tensorflow-gpu'])\n",
    "#pip.main(['install','keras'])\n",
    "#pip.main(['install','h5py'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\envs\\Tensorflow-GPU-Keras\\lib\\site-packages\\h5py\\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from keras.applications.vgg19 import VGG19\n",
    "from keras.applications.vgg16 import VGG16\n",
    "import keras\n",
    "from keras.layers import Input, Flatten, Dense\n",
    "from keras.models import Model\n",
    "import sys\n",
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "\n",
    "\n",
    "def escape():\n",
    "    sys.exit()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening File :  destinationPayload_TestbedMonJun14Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedSatJun12Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedSunJun13Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedThuJun17-2Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedThuJun17-3Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedTueJun15-1Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedTueJun15-2Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedTueJun15-3Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedWedJun16-1Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedWedJun16-2Flows.xml.npy\n",
      "Opening File :  destinationPayload_TestbedWedJun16-3Flows.xml.npy\n"
     ]
    }
   ],
   "source": [
    "import_directory = \"C:\\\\Users\\\\Tamim Mirza\\\\PycharmProjects\\\\Project\\\\Database2\\\\\"\n",
    "counter = 0\n",
    "data_array = np.empty((0, 2))\n",
    "files = os.listdir(import_directory)\n",
    "for file in files:\n",
    "    print('Opening File : ', file)\n",
    "    data_set = np.load(import_directory+file)\n",
    "    data_array = np.vstack((data_array, data_set))\n",
    "\n",
    "#separated = np.array([x for x in data_array if x[1] == 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "source": [
    "#np.random.shuffle(separated)\n",
    "np.random.shuffle(data_array)\n",
    "print(\"ok\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_row = 50\n",
    "img_col = 50\n",
    "\n",
    "N = np.shape(data_array)[0]\n",
    "train_test_split_percentage = 0.75\n",
    "\n",
    "X_train = data_array[:int(N * train_test_split_percentage), 0]\n",
    "X_test = data_array[int(N * train_test_split_percentage):, 0]\n",
    "\n",
    "X_train = np.array([x.reshape(img_row, img_col, 3) for x in X_train])\n",
    "X_test = np.array([x.reshape(img_row, img_col, 3) for x in X_test])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = data_array[:int(N * train_test_split_percentage), 1]\n",
    "y_test = data_array[int(N * train_test_split_percentage):, 1]\n",
    "\n",
    "y_train = np.array([[x] for x in y_train])\n",
    "y_test = np.array([[x] for x in y_test])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_vgg19_conv = VGG19(include_top=False, weights='imagenet', input_shape=(img_col, img_row, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 28800x10800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#ploting images for data\n",
    "%matplotlib inline\n",
    "n = 40  # how many digits we will display\n",
    "plt.figure(figsize=(400, 150))\n",
    "for i in range(6,11):\n",
    "    # display original\n",
    "    ax = plt.subplot(1, n, i + 1)\n",
    "    plt.imshow(X_train[i])\n",
    "    plt.gray()\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "input_1\n",
      "block1_conv1\n",
      "block1_conv2\n",
      "block1_pool\n",
      "block2_conv1\n",
      "block2_conv2\n",
      "block2_pool\n",
      "block3_conv1\n",
      "block3_conv2\n",
      "block3_conv3\n",
      "block3_conv4\n",
      "block3_pool\n",
      "block4_conv1\n",
      "block4_conv2\n",
      "block4_conv3\n",
      "block4_conv4\n",
      "block4_pool\n",
      "block5_conv1\n",
      "block5_conv2\n",
      "block5_conv3\n",
      "block5_conv4\n",
      "block5_pool\n"
     ]
    }
   ],
   "source": [
    "for layer in model_vgg19_conv.layers:\n",
    "    layer.trainable = False\n",
    "    print(layer.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         (None, 50, 50, 3)         0         \n",
      "_________________________________________________________________\n",
      "block1_conv1 (Conv2D)        (None, 50, 50, 64)        1792      \n",
      "_________________________________________________________________\n",
      "block1_conv2 (Conv2D)        (None, 50, 50, 64)        36928     \n",
      "_________________________________________________________________\n",
      "block1_pool (MaxPooling2D)   (None, 25, 25, 64)        0         \n",
      "_________________________________________________________________\n",
      "block2_conv1 (Conv2D)        (None, 25, 25, 128)       73856     \n",
      "_________________________________________________________________\n",
      "block2_conv2 (Conv2D)        (None, 25, 25, 128)       147584    \n",
      "_________________________________________________________________\n",
      "block2_pool (MaxPooling2D)   (None, 12, 12, 128)       0         \n",
      "_________________________________________________________________\n",
      "block3_conv1 (Conv2D)        (None, 12, 12, 256)       295168    \n",
      "_________________________________________________________________\n",
      "block3_conv2 (Conv2D)        (None, 12, 12, 256)       590080    \n",
      "_________________________________________________________________\n",
      "block3_conv3 (Conv2D)        (None, 12, 12, 256)       590080    \n",
      "_________________________________________________________________\n",
      "block3_conv4 (Conv2D)        (None, 12, 12, 256)       590080    \n",
      "_________________________________________________________________\n",
      "block3_pool (MaxPooling2D)   (None, 6, 6, 256)         0         \n",
      "_________________________________________________________________\n",
      "block4_conv1 (Conv2D)        (None, 6, 6, 512)         1180160   \n",
      "_________________________________________________________________\n",
      "block4_conv2 (Conv2D)        (None, 6, 6, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block4_conv3 (Conv2D)        (None, 6, 6, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block4_conv4 (Conv2D)        (None, 6, 6, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block4_pool (MaxPooling2D)   (None, 3, 3, 512)         0         \n",
      "_________________________________________________________________\n",
      "block5_conv1 (Conv2D)        (None, 3, 3, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block5_conv2 (Conv2D)        (None, 3, 3, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block5_conv3 (Conv2D)        (None, 3, 3, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block5_conv4 (Conv2D)        (None, 3, 3, 512)         2359808   \n",
      "_________________________________________________________________\n",
      "block5_pool (MaxPooling2D)   (None, 1, 1, 512)         0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 512)               0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 128)               65664     \n",
      "_________________________________________________________________\n",
      "predictions (Dense)          (None, 1)                 129       \n",
      "=================================================================\n",
      "Total params: 20,090,177\n",
      "Trainable params: 65,793\n",
      "Non-trainable params: 20,024,384\n",
      "_________________________________________________________________\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\envs\\Tensorflow-GPU-Keras\\lib\\site-packages\\ipykernel_launcher.py:6: UserWarning: Update your `Model` call to the Keras 2 API: `Model(inputs=Tensor(\"in..., outputs=Tensor(\"pr...)`\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "x = model_vgg19_conv.output\n",
    "x = Flatten()(x)\n",
    "x = Dense(128, activation='relu')(x)\n",
    "x = Dense(1, activation='sigmoid', name='predictions')(x)\n",
    "\n",
    "my_model = Model(input=model_vgg19_conv.input, output=x)\n",
    "my_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_model.compile(loss=keras.losses.binary_crossentropy,\n",
    "              optimizer=keras.optimizers.RMSprop(),\n",
    "              metrics=['accuracy'])\n",
    "\n",
    "batch_size = 32\n",
    "epochs = 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 481676 samples, validate on 120420 samples\n",
      "Epoch 1/2\n",
      "481676/481676 [==============================] - 804s 2ms/step - loss: 0.0454 - acc: 0.9900 - val_loss: 0.0420 - val_acc: 0.9908\n",
      "Epoch 2/2\n",
      "481676/481676 [==============================] - 805s 2ms/step - loss: 0.0424 - acc: 0.9908 - val_loss: 0.0431 - val_acc: 0.9908\n"
     ]
    }
   ],
   "source": [
    "hist = my_model.fit(X_train, y_train,\n",
    "          batch_size=batch_size,\n",
    "          epochs=epochs,\n",
    "          verbose=1,\n",
    "          validation_split=0.2)\n",
    "score = my_model.evaluate(X_test, y_test, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 0.04166916962365522\n",
      "Test accuracy: 0.9907274077100534\n"
     ]
    }
   ],
   "source": [
    "print('Test loss:', score[0])\n",
    "print('Test accuracy:', score[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1b60a35cf98>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "training_loss= hist.history['loss']\n",
    "val_loss= hist.history['val_loss'] \n",
    "training_acc= hist.history['acc'] \n",
    "val_acc= hist.history['val_acc']\n",
    "xc=range(epochs)\n",
    "\n",
    "plt.figure(1,figsize=(7,5)) \n",
    "plt.plot(xc,training_loss)\n",
    "plt.plot(xc,val_loss) \n",
    "plt.xlabel('No. of Epochs') \n",
    "plt.ylabel('loss') \n",
    "plt.title('Training Loss vs Validation Loss') \n",
    "plt.grid(True) \n",
    "plt.legend(['Train','Val'])\n",
    "\n",
    "plt.figure(2,figsize=(7,5)) \n",
    "plt.plot(xc,training_acc) \n",
    "plt.plot(xc,val_acc) \n",
    "plt.xlabel('No. of Epochs') \n",
    "plt.ylabel('Accuracy') \n",
    "plt.title('Training Accuracy vs Validation Accuracy') \n",
    "plt.grid(True) \n",
    "plt.legend(['Train','Val'],loc=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total length =  200699\n",
      "Anomolies =  9433\n",
      "Normal =  191266\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "checking_occurences = [x for x in y_test if x == 1]\n",
    "print(\"total length = \",len(y_test))\n",
    "print(\"Anomolies = \",len(checking_occurences))\n",
    "print(\"Normal = \", (len(y_test) - len(checking_occurences)))\n",
    "\n",
    "n = len(y_test) - len(checking_occurences)\n",
    "a = len(checking_occurences)\n",
    "\n",
    "label = ['Normal', 'Anomaly']\n",
    "samples = [n, a]\n",
    "\n",
    "default_dpi = mpl.rcParamsDefault['figure.dpi']\n",
    "mpl.rcParams['figure.dpi'] = default_dpi * 1.5\n",
    "\n",
    "# this is for plotting purpose\n",
    "index = np.arange(len(label))\n",
    "plt.bar(index, samples)\n",
    "plt.xlabel('Payload Types', fontsize=10)\n",
    "plt.ylabel('Samples', fontsize=10)\n",
    "plt.xticks(index, label, fontsize=10, rotation=0)\n",
    "plt.title('Samples identified by VGG19')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions =  [[0.0000000e+00]\n",
      " [3.0254741e-36]\n",
      " [1.3322988e-25]\n",
      " ...\n",
      " [0.0000000e+00]\n",
      " [0.0000000e+00]\n",
      " [3.3234162e-21]]\n"
     ]
    }
   ],
   "source": [
    "predictions = my_model.predict(X_test)\n",
    "print(\"Predictions = \",predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 =  [0.99511683 0.9082935 ]\n"
     ]
    }
   ],
   "source": [
    "rounded = [[round(x[0])] for x in predictions]\n",
    "from sklearn.metrics import f1_score\n",
    "result = f1_score(y_test,rounded, average=None, labels = [0,1])\n",
    "print(\"F1 = \",result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 macro =  0.9517051657706019\n"
     ]
    }
   ],
   "source": [
    "result = f1_score(y_test,rounded, average='macro')\n",
    "print(\"F1 macro = \",result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 Micro=  0.9907274077100534\n"
     ]
    }
   ],
   "source": [
    "result = f1_score(y_test,rounded, average='micro')\n",
    "print(\"F1 Micro= \",result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 Weighted=  0.9910360711649695\n"
     ]
    }
   ],
   "source": [
    "result = f1_score(y_test,rounded, average='weighted')\n",
    "print(\"F1 Weighted= \",result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "     normal       1.00      0.99      1.00    191266\n",
      "    anomaly       0.85      0.98      0.91      9433\n",
      "\n",
      "avg / total       0.99      0.99      0.99    200699\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import sklearn.metrics\n",
    "target_names = ['normal','anomaly']\n",
    "print(sklearn.metrics.classification_report(y_test,rounded,labels = [0,1], target_names=target_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_model.save(\"FYP_Finalhd5.hd5\")\n",
    "my_model.save(\"FYP_Finalh5.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----- activations -----\n",
      "(1, 50, 50, 3)\n",
      "(1, 50, 50, 64)\n",
      "(1, 50, 50, 64)\n",
      "(1, 25, 25, 64)\n",
      "(1, 25, 25, 128)\n",
      "(1, 25, 25, 128)\n",
      "(1, 12, 12, 128)\n",
      "(1, 12, 12, 256)\n",
      "(1, 12, 12, 256)\n",
      "(1, 12, 12, 256)\n",
      "(1, 12, 12, 256)\n",
      "(1, 6, 6, 256)\n",
      "(1, 6, 6, 512)\n",
      "(1, 6, 6, 512)\n",
      "(1, 6, 6, 512)\n",
      "(1, 6, 6, 512)\n",
      "(1, 3, 3, 512)\n",
      "(1, 3, 3, 512)\n",
      "(1, 3, 3, 512)\n",
      "(1, 3, 3, 512)\n",
      "(1, 3, 3, 512)\n",
      "(1, 1, 1, 512)\n",
      "(1, 512)\n",
      "(1, 128)\n",
      "(1, 1)\n",
      "Displaying activation map 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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08WJB3cepqylXr5wU4nsiSgXYMM08BoBF7A2gRpQU2e3dYuloPCMFtbFt6lCJae4HAGlJR0VsMwozzYsANjDyxLwIYNHyjRVvoJp+E1lwinzjemExYkRpPn6m6VBOjsVgMLAU5VIOHvvV9wGAvLwLlNv//D9FvGQvL2KwJW0P5T5YL9ewyDrH23nvnXLubFw5kmoG1e9PuaPZUrj95dH1VJNfyAZ8XWtK8aHt2rS0NS+2kJopx2etnixmjWrEBlire8j3spkC5hfyPp+fKBeYGH/rWKqxGROahmktZvWjGpvI1jy3n5zLQvXtIxZTzjTzM8cYAOwf/76Im0xiAeiDt7NfqmnKaRpyAnZTzrdnyH3VLKwZ1QzZwN9v1345pmzGlpsH8Zxr7oOfzvAcbxPid5wjBe4553kBgTJBfJ05MFLO3wv28DZ9doAXnLi7mpzj+yVMpxpzoYpl+1hAfKGQ72VaRcjFMrqtSaCaWS1YHBy/US48cDo7m2oaVqpEue51uojYJmL271qfcsiV59+0F6RR6PiHX8Xx/Sf+vzcmUxRFURRFURTlOqMPBIqiKIqiKIpSjNEHAkVRFEVRFEUpxugDgaIoiqIoiqIUY/70ouKykaFxnRc+KfLT50nRq+kECQDt4tm9dO2kaSJu1bMX1ex/dy3lrkYcDLBA2CYOTp6wQsTNJvegGtvrvPzkirOFh1lUFFyTBXyZ56SAZs/Yd6nGJgpb11u69FUfzAK3VSNZhDb0Ayk+KihgsWfKN+zSF14vQsRpiWlUE9UgknKlAqTj8OE0dj2MCC9PObMu4/BpqiFBJkCutT5BJakkcbQUScU8di/V1HmYHXF/2MSiSXrvGSso98jbcuwn7WUXW5xlMZk5rv18fa74+QCwY8DfRRz7GjtdJg1j5+fAx+V3NsWJABDTuTXlatwjhWqeiIMBFgh7Ig62uRKb5ywAxDwnz4fkv7E7Zdt5gyhnng82caAN01nb5si5bPjzlOs0Qbp0ejJeAR6zRTleaw/7C+XCI+XcZTq6A8D+uSzcrv6sdM1FLosRzXnR5vbtE8ZOrBHGAgmmeBcAYnq1o1zyrFUirj2WReKVKrCrdOnSUqSdtO8I1VxIO0s5c0GGkOrlqMTPh8/t3AtSaJx+/AzVJL/+PuXMczS4Pl8fi0ocDLBA+NQBnuPDosNEfHy7ZQ4sy2PfPB+s58LIjvxeJnszKBXSmF1szeNg207bddwcs56MV4DHrCfjFeC5KzePz6tDluMXZSzksL73HKppPkfeh/3e9wjZloUHci0LHZgLlCRZrjvhtdkdesNzcrEMmqM+OQSczVNRsaIoiqIoiqIo14Y+ECiKoiiKoihKMUYfCBRFURRFURSlGPOn1xDE1KwR98U30hTjevecedqX/sPKbTJRnk2yTHIWb6fc50fY1KluqDSIaTKZjVeOW77fS0OeEnHzCDZQSc/l3tEHJhpmWpYedE+0HOYx+CXMnvPANnH8eRYjmz5LpIndur4zqMbWNwljDPmEs/nc0fGfUi56nHyv4y+xUVjsRNkzOK1TT6oZtIJNz8w+xn3D/0k10RPaUI723ePc7+1Jv77Zqw/8Qr++YWT1R+1LN436bH23e8ZITQ31e8LeYxseIA3xmi99mmq+7LKQcubxsxn3LdyykXI7d0kjO29v/ttQaJkgynlyXtnmKbM31jYW/Z9lo6esmVvk593PbbJRLWpSztSlhI9pRTWmjgIAOtxxs4invMfnrFcJua+CAthQLW0Ma8kCuzWSCYuBW0gI73OzT9zs1Qc869e36Wk86dePfJL33R+xL902t9iuF6a2yRwrALD6sNSXNKrQiGpufOUJymXnSC3g2YlfUY2NTw5+KOJu86ZSje3aUHqovP5eOJ5FNbbjEGjck6Qns5GmDboHsmhzrJhGoZb7FJtp3apXXxFx/IcLqGZTT5mrP6kT1dgMRs0eflv/vlW7ZpzH11uDemLaVuSfzFYNgaIoiqIoiqIo14Y+ECiKoiiKoihKMUYfCBRFURRFURSlGKMPBIqiKIqiKIpSjGHXnD8ZyYcPIOKRO0XONBgyhUAAAD9vSqUdkcIbm9DJNBgC2GTIZjBkM7dAWT8R2kQvprC59mQWFZqiZoCFzTZR81dz36ScKZLsNOsRqmlQrjHlACkqNo1fAGDRD59TzhSvXihkQZ2Xw8+1QzaNloloFvmaAmIAyMqWxyE1M5VqbCKtCqHBIrYZPdnETqZQrP70R6nmrcfleOk4h0VMR8d8QTkT//58XHYnLKWct5ecFkwxFGDfLzkfSQFv508HUM3eFIsQv1olEdsMhrwdPh/L3yqFuD9sTqKasJqVKGea99gExFZh8+tXNoh76J2hlDOxiSZNYfOWjTupJiypOeVM4e/TNXlxgMoBfK5N9JVz0rGjbK5Vrlww5Z5YM0TEics/ppqo0jGUS82UAr5xX4+nGtucW+8N43yIYtFt4qAPKeffVwr/pvV+hmpeXPYe5aYYc/rumSw4rdVTzvHHl27mz+/A+r7Et+Q+fy+ZzedGNIqnXMrZZBEXugVUU2DJmXPlqwm9qSakJM+Lkd3ukzVxPH5M00wAQLAU69oWArAZZ8YMby9irwosAI15+n7+OFPYbBHGn/yJDb5MYfPRbBbGPvaCvF7ZrvXmnA/wvYT/EzdSjU1Q6+ctr/U2wXvYKD7/x3R5TMQp6Xzdeb4xH/fs/HMijg7mBSAWJy+kXI8ZfM0kLIsKmHO8bb/YzCDbjXpBxGvHT6GaFft5UQiTuOosLv+8u1ww5KDlmhbYibdz51wp1i/hxSZ9u+fwuU3vs5hrpm+fx4UWc8vfCv2FQFEURVEURVGKMfpAoCiKoiiKoijFGH0gUBRFURRFUZRijD4QKIqiKIqiKEox5k/vVIwQvzh0jhb5h++7VcRfb5eiLeB/cOAz+PR1dr8d8MFsEWdl5VBNgzrVKTf9nuEibjaVhXEmNgdQm9A4ZVuqTFjcmk1XYoCdiXelsxNs/NLFlHu1s3R17DFmEtXY3H1TxklRn00813wWi6ZS06S4qvDYOaqxuViaIrSoaiyoM8VIANDirT6UM3n1oa6UM0VTXmVZTHZukhQtnshhYa5tH0RUk6K79eu+440y3HcBIHWmdOlMPsPnx9YT31OuZVUp3g/1Y1dSU8wGAHV7dZCJ0yzyX7tgDuW6LpooYpurdM3RLBiODJf7JWXnQapBLo+zh5+4R8T9b3qMau6K78vvZTDwGT4fp8w1hLEWIVnqRBbPDtsgz6NXbmMhd5sFAylnzkHmggkArGPDFPW1msAiWFNACADpZ6WDavqu41STuohdOiO7tBRxcB0+HzP2sfN7zlIpyvZvE0s15ZtUpdyGgbNE3G4Rfz+TpL18rfBkH2yLf5tqIjveQ7nwW6NEnPBYZ6rpFP045fquk9cPm7j0YFYq5WZ/LwW0r90xmLdz4IOUy5n9rYht+zykcRXKZRkLapguugCQvv9Hyq0a/7KIUzIOUc3mNHYvXj5ntYjXzuB5o/2scSLOOH2WasIsrsu9W8vx2imGF92wXcPazpX7+F+9WLwbOZwXLDGv2znTv6ESU2APALE15YIMtnsSc8ESAEAJR77PTXzfkpPD4uCCAvmdj506TTUpCSzgN+957rulHtV8tFGOuyXPPE81rV7mxR482Qe2z1u9ZYeIvb15MYRDX/ACF93i5ViIv7kn1eQW8OIyQb7yvsjcJ+pUrCiKoiiKoihKkaAPBIqiKIqiKIpSjNEHAkVRFEVRFEUpxvzpjclQUAickr1hKz/ZJOLgsty7bvagAhYzjWA2pOg0+xXKrewzRsSVSlWmmgfnc4/bsaZHRby6F/fdZ+XLvtR6U7nP8K0u3ANasbvsxbWZ3bR9cxjlhg6V73Vbf9Y1mGZiAHDL691lorQv1dho8sbTIh79SAeqOXqS+xFXD5HHwdZDaJqQAcCKfiNEfDKHe1cjBrSlXEhYGRG3bMqGJvXLNaCc2SteqXxZKjF7gTPzuEezUW3u5ewcJ41s1q/m/tKQaqGUO5Ile6JDS/I2jVzwLuWajbxZxEE+vJ3Np/ajXOo82dMbOZR77E29AMA9rjbDL9PcDwDyjb7b3dPepxpbL+fpXDnOei5nkxyzp3ZW+/5UYzPSWx67VcRLnuY+2NTMA5R7tr78ztUH8/lvjk0AWNpDjqnWQ9gs0bbvWnXtecWalALuPTbn2JzliVQTO/EBylVtKvfn9oFsJrb55FeUMw3+Vs3hudNmTLjxmLw2HLRoKz7q/5KIbXqaIN9SlDtzXs7Vtp7wqrfXoJy/v5wr64XWpZpvT7E52mffyH3cvR6bVpX143N72x45ztbe8BnVlCzD32/jsXUiDr+D5yTbnBsbLXUFCW2eoJp+y1hDFP/hAhFnZLA+6f0eYyg3dpHUUpzIYT3L6v6vitjfm8228gp5fuu0cKyIbw7jHnRTUwgAk9vL62hFfzYhNe9jAJAJ2JNr+Dy2aY/MOTa8SgWqsRnEmVq8pC2s0dg5fRnlTOMz/848hvMKeH+aWs55lvPRnFtur3Q31XR7tAXlzOvoXdW4BX/0cv4uZYLZmNRk02LWB+W7UpNl07dtGP4G5ep2lXPZt/Pktbf94i5IOcnXhqtBfyFQFEVRFEVRlGKMPhAoiqIoiqIoSjFGHwgURVEURVEUpRijDwSKoiiKoiiKUoz50xuTVa0RETfni7+JvCnqsRlG2QRnpqC13/x5VGMKzgBgX0aKiKd+zuZhN1Rlw53/fLNbxJsGs4GKaXJyLPsY1bTubjFLqigFQ6teSqCSdvEjKJc4W5qHvJe8kmqers0mOecuSDGSTcRsM2zx8ZKCuo9TV1NNvXK1KOfJMb434n7KBQxuIrcznw3bakSx4GuvKa46wwKp2DZ1KEcGUUlHqcY0CvPEvAhgAyNPzIsA4MaKN4i438RZVIN8y7xhmNbYhONVq1SkXNLQf4jYJjizCdVjehjmSBaBq23BgOMv/Ut+nsW4x/Y6E5sh1rcz3hFxSYsYMap0DOX8n71JxOGRvJ+aNahJuUl3SuH/wcxUqrmtTzfK7ZwrhdQlvHiBBE/IL7xAufmJLMQbf6sUW3p6jFvMkiJ0U2AL2M/tJ+dKg8jtI9gs0Wbml3JQzp/7x7PgvMkkuT8fvP0mqjHNiwA2MLKZF709YyzlmoVJM8ghG9j8ctd+NkczRbabB/H1yrYPfjqTKd/nZAbV2ITq5kIKVkMzy4IBpqA1ugabl238N+9PmpsthoameRkARAZFUs6k7Wx5XtnE0BkHfqJc7C3SBPX7vmy2ZTOWrDFK3lvsGLWIaiKDoilnCrlt2ES2nT+VBoYrP9xINR4tRjCe7xFsc+d38QtFXL0vG9uFx/JiK9nn5TEt4cV/wz51Ml3Ed97dkGo8MeU0r7OA3ZTzrR3yelUhIIBq0jIzKbdy9b9FHG4xtot/kM+PfjPnyoS3sQ+W7gPSc/84xmSO49zkOM5wx3E+cBwnzXEc13EcPoP4dX91HOdrx3GyHMc57TjOPx3HufVKr1MURVEURVEUpWgoqmVHXwTAjza/guM4kwEMBJADYC2AkgBaAmjlOE5713X5T8+KoiiKoiiKohQpRfVA8B8A2wFsvfQ/Xtj3ZziO0xwXHwZ+AtDUdd29l/JNAXwJYIHjOF+6rpv+y++iKIqiKIqiKMq1UiQPBK7rChcPx3F+qfQyl5sLEy4/DFx6n/84jjMbQD8ATwNgNxlFURRFURRFUYqM30RU7DiOCyDXdd2Sln8rCeAMAD8AEa7rHjH+/XYAGwCsd133rmvcjkTv8v5xZXtJh9igQOmyaArJALv4MS9PCuj2P8/i4CV72aFuS9oeEX+wfivVZJ1jycW9d0pxTOPKkVQzqL50Qj2azeKyL4+up1x+oRTwdq3JwkNTeAQAS1tLJ73UTHYqrNWTHTijGknR6+oe7MhXuVQE5WJfk+KjpGEsPAx8nB2ATYFiTOfWVFPjHhYj/5biYNOVGACSJ6yQ2/kc77vkv8nuubbz2I2yoIDFz6Y40EZgKTpFkZYqHU2XDWfX3E4TxlPOJ0i+V+Lod6gm5rF7Kbd2gXQh7TiHBe455/k4lAmSYq4DI1lwvmAPCyk/OyD32HcbAAAgAElEQVRdyO+uxuOgX8J03gbDvXzZPv5+FwqlUK1VREuq6baGv9+sFlLEGL9xKtWczs6mXMNKlUTcvU4XqrGKmLvWl4lcFvRPe4EXIxi9fLmI/XxYjJx7gYXG6cfPiDj5dRbr2s7R4PpSaPhbioMB4NQBKRQPi+bFHo5vN+bYsnwOmecCwOdDzMiOVGNlrxT1hjRm0a3tOJjbGVyTr2k2YaxPmHRiPTuRnaD9O7B+MbxhNREHBrKg/vV27Gz/SYoUtCaeYDfate3nUs5cAKLr/XdRTag/OyqPbTJKxIez2OU1O18KskuVYOHo50f+Rbn082dFnHGe5+CedZ+i3IhN8nq45it2v946jOeyad/PF/H0ef+gGk8WDFk7aRrVtOrZi3L7310r4t9SHAzw9bHZ5B5XfJ2XH19nCw/zcTDPh8xzPL/uGfsu5cyFDtb15sVebI7xq0bKBQOGfsDH03YdT/lGLkoTXk/eJ52YthX5J7P/OKLi/5GauPgwcMp8GLjEZTk4e34riqIoiqIoilKkFJWG4H+h6qX/2h4G4LruOcdxzgAIcRwnyHXdK/6Z03GcxF/4p+pXuY2KoiiKoiiKUiy4Hr8QXP49kn+f+S+Xf68L/JUaRVEURVEURVGukeuhIegC4B0Am1zXvf0XXp8GoDKAyq7rcoO/59uR6BcWGFfjxbtE/odNe+wv+BmJM1ZQrvawv4jYZh6UtoN7+PfPlYYX1Z99gD8wN59SZo+bJ/2eERazC1u/fkyvdiJOnrWKamqPZSOrShXKirh0ae7RTNrHP/5cSJO9lWSuAVh77K+2L73Ow1JX4MkxB/i4m8ccABmaAHwc9ozh3kPbcTf3e3hANappvvRpEX/ZZSHVRE9oQznT5GThFjaf2bmL+2e9jWMTWiaIaqxajjZxMlGee4jDa7Opm5+v7H/2ZLwCvO9s2orcPD5Wh4z+8iiL0dz63nMo13yO7Km9mn5PAEhLZGOiqAaRIi4VwD3o2RadUa6ha7L1bSeZuhjwcdjw3Gyq8WSeutq+9KKcp2zH3dQC2Y6DOe4AYMcAaSS1+jCbFTWqII3sbnzlCarJzmGTLFsvvsknBz+kXLd5Uk9iGusBQOmhzSh34XiWiM1jAACBlnGWnmz08FvmanO8AjxmD6excV9EeHnKmXUZh09TjdUI0bheeKLbAPh6YV4rgKu/R3jkbdmbn7SX7wdwlvVQZt+9bWzaMOcpc44Cfv95ypPj/sPKbVRju16Y5CzeTrnPj0jtWN1QNj1sMpn1QseN7/fSkKeopnkEn1fpuVIP9cDEUVRjO8amlsNm/Go7DibmtbfRjbdgz+49/99qCC63ALFK579cvsvM+pUaRVEURVEURVGukevxQHDo0n95qQQAjuMEACgD4Iwn+gFFURRFURRFUa6e6/FAkAQgF0B5x3FsDwWX19rc8fttkqIoiqIoiqIUT373BwLXdXMAXG6CfMxScjn38e+zRYqiKIqiKIpSfPndRcWX/r0FgM8A/ASg6WW3YsdxmgJYh4u/INzguq5FXfQ/bUdirbhacd/t+Ebk/Z+9ScRZM7fQawPvZ31GVIuaIjYFaAAQPqYVv5dh/tThjpupZsp7n1LOq4R8XgsKYAFv2hhpFBLYrRHVoLQvpUJCpFBUDYYuYZgM/RGEaqawObhCMNXYhL+eCCQnblpJuWNHpSi0XDn+vGphLApNaCaPn80QyxMjO6vAzSLWJyziR5sIzb+zFJ2tevUVqon/cAHlNvWUufqTOlGNKer1RNALsFDMdh4XN4MhgE2GPDEYAljYbBPUeiJsvloxu01UbIo0PRFIAsCz78hjmpXN4vJhj7AAPCVdGgw+35jnV9OACwCig6VRn/99fB6vmjuZcn2WzBTxur5s2GTbnzBErz7hpank6Hi+PkaPk+9lE1vHTuT9Mq1TTxEPWsGmZ6ZYf99wNiG1LeRA57EHppkAXzM9Ms0EyDjTE9NMwGKc6YFpJsDGmaZpJuCZcaYpagY8EzYXpZj9w8cnitiTRT8AXvgjYEATqgkzFl8BgKYN5f3jq7f3p5oLhXzP5eXIOXbqNnkdeq/r20g/eLpIRMVF4kPgOE5bAC8aaV/HcTb/LB7nuu4nAOC67ueO40wF0B/A947jfAbAF0BLXPzVosu1PgwoiqIoiqIoinJlisqYrDyAW4ycY+TEI5rrugMcx/keQF9cfBC4AOALAAmu624qou1SFEVRFEVRFOVXKJIHAtd1FwJY+Hu9TlEURVEURVGUouF6rDKkKIqiKIqiKMofhKJqGfrDcirnFMZ9PV4m/bxFWO+NR/mFUSzSTBwkXST9+7Lwb1rvZyj34rL3RDzFIlTZPZMFyqbY8vjSzVTj30HqSBLfYpHPe8mcG9EoXsQpZ5OpptAtoFyBkbOJYF5NYPFaSEkpFIvsdh/VWDktxXn7z+6nEl+Lq6Mpdqo5mh2Ho5pEUy5l50ERXzh7lmriN06l3JdvzxfxXfF9qQYlHEoNfEa6Cdfu34FfZwi+bILsYRsmUe5EjhSOjfzH21RjFZwdkU6lh3axoHfC+CmUq/2idLaOqlaJatLPstfgm2MGi7jHjJlUY8VwtrR9nv8TN/LrDCFeu1EvUMlay/dbsZ9FdiZx1aUw7vPuLKw8mJlKucBOcjt3zmXxfAkvHue75/C5bbJzMddM3z5PJiyiQhvb4uUYihzIYuSc2d9Szr9NrIhDGvOK0z7+fpQznXTT/Xi8LnqGRYwpGYdEvDmNBZnL57CAN/UvqSIOviGUamKGtxdxmEWc3Lt1S8p16vuI/CyLwL7/8lmU+6q/FL1GDn+Yaka+tYRyOdONxTQs16vYmuyMTnNCNIt8TQExwGLnVMs4t4m7K4TKRQvSUk9QjU3Ab4qI60/n6/hbj/PY6DhHivOPjvmCakz8+zem3O6EpZTz9pLnkU3kb9svOR/JBSc6fzqAavamsHOwOQea8w8AfL2dr+3ILfj1GEBMDz63P31diskfWDiEamyC+gZ1qov4X714/DSbyvdO5gIM5j0YANSeLK+hNqf0jH0sNF5ys5zPN01md/ovj66nXPxSef19sw/f7/QYw9fjj8/IBRGm3c3OzL4uLwBjLraSmibPj8JMXhjgatFfCBRFURRFURSlGKMPBIqiKIqiKIpSjNEHAkVRFEVRFEUpxvwmxmR/FBzHSUSQTxxayj601EXSlCeyC/d7BtdhIyuzDy1n6U6qMXtlAaB8k6oi3jCQ+0TbLYqnnEnSXu7lNvumbT3aZt8vAER2vEfE4bdGUU3CY50p1yla9on3XTecamwGOAezUkU8+3vWUbx2x2DKRQ6V/YHhVSpQjWleYqUs9ydXrcKGRmuelb3juQVsAnQ6ly0yeq1gXYHJrPZsRGKajnSZP55qljz9/BXfu9AtpFzz0QNFHBJWhmqW9uDj13qI0Xdr2XfYx9oKqrO8Lrgs9yNTz6dFaxF7U3XK5eRILUBBAffBHjvFxyolQep1bL2r991Sj3IfbZS98Uue4ePS6uWhIvaoR9vyeau37KAab29vyh36IknE3eIfoZr4m3tSzhzXQb58XGz7ZfQjUuPSb/48qvmo/0uU67pImgDZzLVs5kEJbZ6Qn7eM+3z9/bnvNiND9tW+32MM1YSW5N7/EznHReznzWPY31v2/uYV5lFNp4VjKTejk9QVDfhgNtW8+lBXyt0bcb/8fMNYDwD1kgNAhza3idiT+RXgOdZmCmgzkTr5U4aIo6rxNdSmqWnxVh/Kmdj2i6n98SrLJpLnJrHu7kSOvF7YDDEjqslrw/p13/FGncunVOpMaf6YfIb797ee+J5yLaveKeJQPx6bNhO5ur0MzZmHc66pv7BqrYJZs2S+18o+Y6imUik2NHxwvpwX336c587AEqwvycqX9zN/fYevj3M6yetcRX8edzY9ZNs3h4k4aeg/qMZ2rpnGcre83p1qTANXgE1OTe0MwPMrwHOsOb8+c09vHEw+VCTGZPoLgaIoiqIoiqIUY/SBQFEURVEURVGKMfpAoCiKoiiKoijFGH0gUBRFURRFUZRizJ/emKxWRDS+Wy4NWmInPiDiqk1ZsLh94HuU23zyKxHbjFBWzWFDCtPEZeOxTVRz0DCDAlg8YhMjBfmWEvGZ8ywqthnZVL29hohtwrx6oSyo+faUFGl99k0i1XSvx8YyZf3KinjbngNUU/HecMqZxmTrJrAozWagYoqrgoNZsGQVERnmPTZBlg1TcP7tjHeopqQ3C/+iSseI2GbKYwqNmzWoSTWT7hxGuU3j5L66rU83qqkSwAZRnphd2cg3TOrmJy6jmvG3stgyYHATERceY/Fc0hY2cdo5Xb5/dHAtqrGJwvIKpAjUJpqcZzkfzbFwe6W7qabboy1EnJnHgtO7qrH2a/Ry+V3KWMarjU2L5YIB+S4LHW2mfBuGvyHiul15Lvt23ruUu2nE0yK2CdXf2sHnFZlrWcSsgaVYFDrlayngO3KcDYYK81lQb84bP57/kT/Ph/dxGV/5fdrO5vPKFETbjJBib2HTw7sqy8Ur1nSLo5oao1hUuGOUPN9ti1lsPLaOciYV/Xl+fbjtbZRb+eFGmbAIVW2i8BX9Roj4ZA7v84gBbSlnjqGWTVngWr9cA8qZZnqVypelEtuiF+Y52ag2X/87xzUX8frV31BNSDU2rTuSJeeS0JK8TSMX8HnVbOTNIg7y4Xmj+dR+lDONwjwVqkdPaCPiN18cSDW2BQNW9HpRxHvS91KNbYGN6jdIofF9U3kRlU2D+dpuCvintWcBePOuxuIHFfk6u+qlBMod2pYqYps566hBj1PO11veK20axIvEeGLq6uPF91wfp7JZ4sp+o0T83N+ni/jYWV4442rRXwgURVEURVEUpRijDwSKoiiKoiiKUozRBwJFURRFURRFKcboA4GiKIqiKIqiFGP+/E7FpX3icJ90VTSd5lrMYrGOTWRrinOenDuZaraPWEw50wkx5eAxqtk//n3KNZkkRaAP3n4T1ZiOpp64mQLA2zOkuLNZWDOqGbKBv9+u/VI0ZTqCAsDmQSxGMvfBT2cyqcYULAFAxzlSDJRznsVWZYICKHdgpBTnLNjD2/TZARbn3V1NClP7JUynGpuob9k+KSK+UMjizlYR7IjdbY38frNasIgxfqMUaZ3OzqaahpUqUa57nS4iNgXMAODftT7lkCvFT9Ne6Eslo5cvp5yfj3S2zL1wgWpsDo6mqNDqnjx+BOVMke938QuppnpfFpyHx0qBW/b5XKop4cV/Kzl1Ml3Ed97dkGrI0dQDN1OAHU1twtwKATzO0zLlebRy9b+pJrwSu57GPyhFvf1mzqUaePM+yJn6tYj9O7BAOrwhuzMHBkqh3+vt2AX5k5SNlEs8IcXda9vzdpqidADoev9dIg71L0U1Y5uMotzhLLnYgc0dtlQJeRw+P/Ivqkk/z07eGeflsepZ9ymqGbHpDcqt+UouJrF1GM9l076fT7np8+QYsgkr28XzebV20jQR2/aB6Z4MWBYHsIi9a0SxsHmvuWDAGZ7jY9vUoZzp+J2WdJRqbOdaZMd7RBx+axTVJDzWWcSdollcahMs31jxBhH3m8iCU+Rb7rlMd/bSfP9RtUpFyuXkGI7jgTzObfcb5nvl5fFcvf/5f1JuyV65iMGWtD1U88H6rZTLOie38947ee5sXDmScoPq9xfx0WxeAOLLo+tFnF/Igt6uNXlBjc6fDhDx0tZ87qVm8mIWtXrKRVqiGvH4Wd2D36tyKXkfGvsaX5uShn1EucDHpaDevH9t0+Qh7NuzX52KFUVRFEVRFEW5NvSBQFEURVEURVGKMfpAoCiKoiiKoijFmD+9hiC6ZvW4f27+UORjOrcWcXB92VMM/LZagFMH2FwnLDqMcse3G/1yZdm4xydI5hJHsyFWzMiOlCP2ZlAqpDGbVpl94rSNAIJrcq+jad7jE8amQBGWXmezFy+mVzuqSZ61inJt5w0ScW4e93Ifshy/KKPHdX3vOVTTfE4vyhUUyH7ZlG9SqCa8XgTl0hLT5Oc3iKSaUgHyGGefY1OgXEsPqNm3bTP3Cq/NPb0bnpPmNtWffYBqkMv70zzuNsMm23G/kCTr9r+7lmp+Sy1A8oQVVNNsco8rvs7Lj30dCw/LPnHbuZB5jjUge8ZKsyKbrmldbzbuqT5Y9rOuGsnGb0M/4J7z33O8AsDhNDnnRYSXv2INAGQcNkx3bP3XAXwcPJoXH7uXcnUelv26P2ziHmmTxBk8fh55m3vzk/Yac+VZ7pU3xzQA+Pn6UM7Ek3nKPOaAZ8c97d9cU+MeNgH8LbUAtmNsnrcxz7EBZ/Lf2GTRvDbY9otN42ZiM9IzjSWXDX+eajpNGE+533O8Ajxmaw9j88LwSJ67TBPH/XNZo+HJ9cKTewSArxdFeY9Qe6zUhVSqwCZypUuzJiNp3xERX0hjvZBNf2WOYfOYA54dd/OY7x33JXKPZ6mGQFEURVEURVGUa0MfCBRFURRFURSlGKMPBIqiKIqiKIpSjNEHAkVRFEVRFEUpxvzpRcU+FQPiIgY3FfmiEqqSiAp2IZ4pCtsx4O9Us/owi3MaVWgk4htfeYJqsnOkkPLsxK+oxsYnB6XQutu8qVRz/CU23Ck9VBqYXTieRTU24WigITRMTz5JNTZI4LaDRcxWDFFPzuLtVOLfuS7lVr36iojjP1xANZt6cq7+pE4iNgW9gGeiXqsxSTc5Dq7WYKhVTxZDeyLgtQkdPRHwmiJcwC7gNc+/ohSq/rByG+VQno+NiW28fH5Emt3VDeXx02SyXEDguCHCBYCXhjxFueYR8rxKz2UDtwcmspGWKUz1dGzY5ikT61hsEyc/z2LO2GfJTMqt6ysF0bY5FxZxp0+4NJ87Ov5Tqokex+9lzl2xE1noOK1TT8oNWiGNz2xi/X3DpWFT9IQ2VHM1BkMAL3gBsIDXdt3xRMBrincBDwW8GbwPbHgiVLUZ9ZnXiz1j3qUam1DVvEaHB7AhXvOlT1Puyy4LRWw7fqZx38ItbJq3c9cBynkb153QMkFU48l5ZZujbAtAmGPR/1k2L82auYU/736pP41qUZNqbPcp4WNayfexCKs73HEz5aa8J89brxL8t+igABbwpo2R1yfzWgiATNxCQnifm4uhAGycaTPNTH6dF4n5wy1K89FBICNPRcWKoiiKoiiKolwb+kCgKIqiKIqiKMUYfSBQFEVRFEVRlGKMPhAoiqIoiqIoSjGG7f/+RxzHKQWgFYAHANwMIBKAN4B9AP4OYLLruqw8vfjavwLoCyAOQB6AzQASXNf997Vu12UKCwuRmSWdQWOGtxexVwUW8MQ8fT/lyF3P4kZ38id2/DXd9Y5mszD2sRdYMGiKpiqEBlONKSr2f+JGqrEJJP28/URsEweFjWpOuTFdHhNxSvoJqnm+cW/KZeefE3F0MDtdLk5eSLkeM1igSFgEWFHVKonYtl9sQrx2o14Q8drxU6hmxX4WxprEVWfR5ufd2Wn2YGaqiAM78XbunCuFRiW8WCC1ew47ctL7LOaa6dvZxdbmCmqyLf5tykUOlGLknNnfUo1/m1jKJS+XYt2rdRy1OTijrB+lTHGe6b4LALUnP0Q5U9hsc9Y1hc1fzX2TamwCyU6zHhFxg3KNqQbgOcJ0OF/0w+dUYxOvXiiUgjovh+eyIZtG8yZES5GvTUCclc3HIdUY57aFB2zzm+n8aor3AfviB/WnPyritx4fRDUd57AA++iYLyhn4t9fHpvdCUupxtuLzyFT5G/uEwDI+YidZjt/OkDEe1N4vNrmQHMO+np7Mr8ut+CKuTCLmNXmUG+KiK1OrK9f2Yn1oXeG8jZZMIXpNsfoLRt3Ui4sSV7XbMLfp2tKIWflgDCqmejLc9Kxo9Jtt1w5HtNPrBlCucTlH4s4qnQM1aRmsph83NeG67GfN9XUe+NRyiFKfufEQR9SiX9fFvBO6/2MiF9c9h7VTLEsyLJ7phQo1+rJc/zxpZt5GzpInWziW7zP30uWuRGN4qkm5SyP/UJXjvMCl88Fc54EgFcT5P1NSMnSVBPZ7T7KEad5YY79Z/dTztdYlMa8FrbZ+hD2ZfDrroai+IWgM4CVAJ6+9H6rAWwEcAOAsQC2Oo5TwXyR4ziTASwCUAfA5wC+BtASwAbHcXi0KIqiKIqiKIpS5BTFA0EegFkAYlzXreO6bgfXde8DEAtgG4CaAMQ6n47jNAcwEMBPAG50XbfdpdfcAaAAwALHcUKKYNsURVEURVEURfkVrvmBwHXdt13X7e267l4jfwxAn0vhI47j/Hyx2MGX/pvw89e5rvsfALMBBOPiLw6KoiiKoiiKovyG/KbGZJf0BZebxyu7rnvMcZySAM4A8AMQ4bruEeM1twPYAGC967p3XePnJ3qV848Lflb2ZWcZvcamaRYApO//kXKrxr8s4pSMQ1SzOY37/JbPkT3Sa2dwL3n7WeMol3H6rIjDDC0CAPRu3VLEnWIeoRpbb1zbuYNF/K9e3AscOdzSuWWYB+VM/4ZKbL2HsTWlaYzVJMfSy40Sjnyfm6pTSU4OawEKCuR3PnbqNNWkJLDxSrOpskfyvlvqUc1HG7k3fskzz4u41cvcB2vuA4D3g+3zVm/ZIWJvb+4TPfRFEuW6xcuxEH8zGzHlFnC/d5Cv7Ik09wkAjH6kA+X6zZd6hI/6v0Q1XRdNpJxpNvfp62x2NeCD2ZQz912DOjw2pt8znHK272NiGv4ArCtI2ZbKLzTOD09MyABgV7rsHY9fysY2r3ZmY8IeYyaJ2DTyAoCUcTzOzTnBNM0BgNQ01gcVHpNaIJvBmU1HFVVN9mDb9DQt3upDOZNXH+pKOVP3AwBeZeWcfm4S9yefyOH5xtwPEdUqUs36dd/JhMVsK3UmG00mn5F9zFtPfE81LaveSblQPznvm3osAKjbi89HUz8TXJbHhk1/YeqtbBq7yHDeLyk7D8qERZ/w8BP3UK7/TVKXdld8X6qxMfAZeT5Omct98DY9VOpEWTdswySqeeU2qdtos2Ag1VivYUcMw03L2LDp0lpNkH3vpgYOANLPshQzfddxEacuYqPJyC4tKRdcR56PGftYD5WzlPUXpgasfJOqVLNh4CzKtVvEff0mSXtZl2LuB9s+MPVskR15jIXfGkW5hMc6i7hT9ONU03cdXz9MjeTBrFSqmf096yheu0Pec0UOZZ1aeBXqrrffF/2cTw4BZ///MCa7fBQuALh8R1YTFx8GTpkPA5e4PNvynZGiKIqiKIqiKEXKNa8ydAX6X/rvatd1L0uqLz9S2h4G4LruOcdxzgAIcRwnyHXdzCt9iOM4ib/wT/wnQ0VRFEVRFEVR/o/f7BcCx3HaAOiGi78OvPizf7q83lw2vei/XP5NlNemUxRFURRFURSlyPhNfiFwHKcWgHcAOACGuq7784XwLzeF/5p4wfmVfyN+qXfq0i8Hcf/LeymKoiiKoihKcaLIHwgcx6mCi14EIbhoSjbVKLncAhTwK29T6tJ/rYZm/yuFhfLZIza6iogT2rBYr9+yOZSL/3CBiDMyWNz1fo8xlBu7SIpQTuQcp5rV/V+lnL+3FHPlFbJ4ttPCsSK+OYylFzZB5uT2UlhZ0Z/NZ3CKRVOmAc6Ta9jwxxRtASygsYlnbOI1U8SYtIVF2zunL6OcaXzm37ku1eQV8P40Ba7zTJEY7OK82yvdLeJuj7agmsw8/ry7qsln2dHL+buUCb7yD2WbFrNRWL4rBW01R/+FajYMf4NydbtKI5tv571LNTeN4EXAQsLKiPitHf+gmq/6z6WcOTY6zX6Falb2GUO5SqUqi/jB+SzkPtb0KOVW95Iiwqx8nmbqTWVB/VtdpCisYnc2KzLNbtq+OYxqhg4dTLnb+svz0WYmdsvr3SmH0r6cM2jyBh8rUxR+9CSL7lcP4eNgiuVtJmQr+o2g3MkcuUhDxIC2VGOOHwBo2VQKXOuXa0A1NuFopfJlRWwTB9rOx0a1ZZdp5zg2Z1y/Wi6kEFItlGqOZLFAMrSk3KaRC/i8ajbyZsoF+cjtbD61H9V4IsS3CbKjJ7Sh3JsvSgGtzRwy3xDPA8DuadJA0bZgwelcHmc9l0uRrW3hiFnt+1PONNNbHruVapY8/TzlUjMPiPjZ+u2opvpgef7bxubSHjymWg8xrocWY8RWXXlxB7MupYCFpLbrTs5y2S0dO5FND6s25f25faA0FNt88iuqMc39AGDVHDl32owJNx7bRLmDxnXUtuCETWQf5FtKxGfO81xtLn5S9fYaVOPvz/NkvVB5T/DtKV544LNvuBu9ez252EJZv7JUs23PAcpVvNe4x7IYk62bwIstxPSQhp80pniNkaumSFuGHMcpB+AzXNQJLADAlnzA5aV5qlj+DY7jBAAoA+CMJ/oBRVEURVEURVGuniJ7IHAcJwjAp7i4itAHAJ5x7WuaJgHIBVD+0q8JJg0v/XeH5d8URVEURVEURSlCiuSBwHEcPwAfAmgEYA2Av7iuZfF7AK7r5gC4vPjxY5aSy7mPi2LbFEVRFEVRFEX5Za75gcBxHG8A7wK4G8BGAI+4rsvNmZLLDY8vOI7zfw1fjuM0BdATwFkA82wvVBRFURRFURSl6Lhmp2LHcfoDuKxMXImLN/M2hriu+3/KMsdx3sBFn4JsXNQd+AJoiYsPKR1c12V7zf992xIR4huHjlJUYwpao2tw59LGf3PHUmG+IaSyiEJMN2MAiAyKvOK2tp3N4kNTsJdx4Ceqib0lWsTf9+XdZnPkrDFKigp3jFpENZFB0ZTbeGwd5UxMgS0AdP5UOj+u/HAj1Xgi3Go9ngWLNrHVd/ELRVy974NUEx5bmXLZ5+UxLeHFz8ynTqZT7s67G4qY3EwBjxxNTTdTgMW5FQJYj5+WyXKblav/LeJwi9N1/IPslthvpiH89eZ9kDP1a8r5d5AC6aVOoxgAACAASURBVPCG7MwcGMjCcU8EZ/syUig39XPpJnxDVRb5/ueb3ZTbNFgKt2xO3seyj1GudXfDQbUif5dVLyWIuF08j9fE2XyOvpe8UsRP12bXzHMXeBEDU8Rs+y4+Xiyo+zhVuqfXK1eLamyLEZjC1Hsj7qeagMFNeDuNubNGFC9isNeyYADOyL8txbapQyVWx9gkKSa3OQd74mhqupkC7GhqEyzfWPEGyvWbaDi45luuvSUsC+wZwvGqVdglOCfH4jgeKAWZKQd5TNveKy/vgnzvXP77ntXh2HCot83LNkyX3G9nvEM1Jb35XIsqHSM//9mbqCY8kr9fswY1RTzpTr72HsxMFfFtfbpRzc6571OuhJcP5Twhv1Du8/mJvLjE+FvHUs5cLMO2GEGLWSxCN0W2NsH5k3NZqL59hHRQtzmc28bZ/vFyXzWZxPvzwdv5+K3eIu/DvL1ZQXvoiyQRvz2D91OzMHaHH7JBfr9d+3khANvCMZsHyb9V2/bBT2f4eryi14si7jgngWpyzvO5ViZIXu8PjJRzd8N6jbB71+4icSouilWGQn72/3lpjv8yBsD/PRC4rjvAcZzvAfTFxQeBCwC+AJDgui7L1BVFURRFURRFKXKu+YHAdd0xuHizfzWvXQhg4bVug6IoiqIoiqIoV8dv5lSsKIqiKIqiKMofn2vWEPyRcRwnMaJGlbiZn0lvtE9SZP964gk2n1rbng2UzN7YrvffRTWh/qUoN7bJKBEfzmLTiux87lUrVUL2jn1+hPs2089LyUbGee5d61n3KcqN2CQNqdZ8xaYgW4exrnva9/NFPH0em0+ZfdQA91KvnTSNalr17EW5/e+uFfFvrQVInrBCxM0m9/DodV5+8se2wsN8HIJrcj9r5rlsEe8Zy2ZFZg/out5sXmIa6QDAqpGyl3LoB3w8CywGQynfyH798HoRVJOWyLqUqAaRIi4VUJJqDqedotzRsZ+LeMleNlnbkraHch+sl0ZEWee4j/reOxtSrnFluZ2D6rPp0dFs7if98uh6EecXcr9+15qyN9bUzgDA0tZsBpeaKfvna/Xk4xnVKIpyq3vI96pcio9V7Gt8ziQNk73GgY+z4ZetHzmmc2sR17iHtQe/pRbAZkJmnrMAEPOc3H/Jf1tJNW3nsamieT7YeoFNAkvxOE9LPUG5ZcOlSVanCeOpxieI3ytxtOypj3nsXqqp8zAfvx828TlD7z2D913tYdLAcOYA7pH+7MBOyt1dTY6FfgnTqSZnKb9u2T75/S4UstaqVURLynVbI68zs1qwFiB+o+mLCpzOlnNuw0qVqKZ7nS4iNvUKAODftT7lkCvnhGkv9KWS0cuXU87PR2oPci9coJr042col/y67M03z08ACK7P18ffUgtw6gDP8WHRUt91fDvPryjLY988H8xzAQBiRnbk9zLZm0GpkMZSO2oeA8C+neZ13Kbt9AljM9EIQ8Nnzt0AENOLTfKSZ60SsTlvHXztK+SdOFckGgL9hUBRFEVRFEVRijH6QKAoiqIoiqIoxRh9IFAURVEURVGUYow+ECiKoiiKoihKMeZPLyr2CwuMq/HiXSJvChszDp/mF9tMYwxBmycCMIBFYEUpAHvkbSnWTdprEeucZbMLU4jr5+uZocr63nNE3HwOC4H/CELViPDyIv5h5TaqQXk2uzHJWbydcp8fWU25uqHSIKbJZBZbHbd8v5eGPCXi5hFsoJKeK8VkD0wcRTW2Y+yJSZbtOJiYAlQACGwTx59nGNn0WTKTatb1ZUH03dP7iDhtB4/h/XPZWKr6sw/IRC6LEW1CblME5okADGARmCcCsNpj2WCsUoWylCtdWi5GkLTvCNVcSLN4PpqmcRbR7R9RqGoz6bMdhz1jpMiejjl4nwNAeIA0xWu+9Gmq+bLLQspFT2gjYptx38ItclGKnbt4kQhvi5lfaJkgEXt6XpnzVHhtNnXbN/yflDONurJmbuHPu591iFEtpHFXvmU+P2QRnEYZZnPmtQLw7HphXisAz64X5rUCsF8vso3FB3LzWMBrGigmWYTytuOw4Tlp5mcbr57MU9dbqArYFwcwj4PtvmHHADZeXH1Yzt+NKjSimhtfeYJy2TlycZCzE7+iGpNPDn5IuW7zWFxumuuVHsrX3gvHsyhnHodAyxhLT+aFakysY9py7SPMueWTQ8DZPBUVK4qiKIqiKIpybegDgaIoiqIoiqIUY/SBQFEURVEURVGKMX96DQFK+8ahbVX5D0bPok94aXrt0fGfUi56nOzFM3vQACB2IvcMTuvUU8SDVrDpma2P0ewLNftbATUYAjwzGPqt+1JNHYOpYQCADx+fSDmzx9STfuiAAU2oJszSl960oewFfvV2NuC6UMjjzsuRfyeYum0B1cxevoa3s0oFEWdls1HYil4vUu7WirfL9xnTimps5k8d7rhZxFPe43PWqwT/zSMoQPbrp41ZSzWB3bjHFaV9RRgSEkQlajCEqzcY8kDH4ImGAWAdA2kYAARXCKac2efvST/0xE08Jx07yj3g5crJz6sWxjqVhGZ8/ExTLNPEDgAW72azq/FL5FwSVY0NuFJSWNeUM/0bypn4d65LuVWvviLi+A953tjUk3P1J3USsdm/D3jWw2/VZFjOY0+0VaZxpiemmQAbZ3pimgmwcaYnppkAG2d6YpoJsHGmJ1orgPvnPdFaAaxjsF3nbNdxU0Ng0xmaOj+bxu/Zd9gI1bw+DXuE791S0tlg8PnG8hy1mcpGB/P91OLkhSLuMYM1djjF906mhsg8jw9P+g8uqDGZoiiKoiiKoijXij4QKIqiKIqiKEoxRh8IFEVRFEVRFKUYow8EiqIoiqIoilKM+fOLisuWjPN5UoorK4RKcVdaKgtHwiNZZGOKfOtPf5Rq/vZoX8p1nCNFTEfHfPHLG/0z/Ps3FvHuhKVUExkULeKNx9Z59N63V7pbxJ0/HUA1K1f/+4rv8/B9t1Lu6+3JlPPIcMPCp69Ls6sBH8ymGpuIuUGd6iKefs9wqmk29Zkrfr7N8Kf2ZDYrStmWKhMWMx/ThAxgI7Jd6SyajF8qhaOvdmYDlx5jJlHOFMunjGOBZIFbwNtkCFNT0/j8KDzGQipTpH3ypwyqiaoWRrmkPQdFPK03H5cXl71HOVP0tnsmf79aPR+mXM7SnSL278BarMS3WCj6XrLMjWgUTzUpZ+XYL7TsX9s+9/GSguWPU1kYF1KSFz+wHXfiNIsY1y6QplFdF7Hg3WYiV3O0FOdGhvM8mbLzIOWQK7/zw0/cQyX9b3qMcnfF83xqMvAZPh+nzDXMiSyLGKROZAOjYRvk/nzlNp4X2ywYKGLrIgpHLMZEhhnb2vFTqKTVBB5Tpogw/SybJaXvOk651EVS9BrZpSXVBNfh8zFjnyEmt5is4SdeMAAVpfjR9v32ZfDiDi+vkudt4xtjqGba3Tx/H8xMFfFtfVgYv3Pu+5Qr4eWZCefPybcsvjA/cRnlpiyVgnNzoQUA+Ko/LyoSOVCKkXNmf0s1/m1iKRfSuIqIs87xcbEaZ+3/UcSrxr9MNSkZhyi3OU2Ku5fP4Xlq7QyeN9rPGifijNNsshhmESj3bi3HbKeYR6jGnE/bzh1MNf/qxQLeyOHGtcFyzbYJ7P37SqF6bM1qVGOdE0xBdAmHamJvqk65nBy5kEtBgfy+J6ZtRf7JbBUVK4qiKIqiKIpybegDgaIoiqIoiqIUY/SBQFEURVEURVGKMfpAoCiKoiiKoijFmD+9qDimZo24L76RwpcWb/W54mtffagr5dqNekHEXhZHznOTNlPuRI4Uk9jcRCOqsThv/brvjDfPp5rUmVLElHyGBb1bT3xPuZZV7xRxqB8LemwOfHV7dZCJsn5UE1yWxY+mq7P/EzdSDYJZ7GW+18o+Y6imUil2g3xw/lARv/3481QTWCKQcln5UrD313fGU82cTgMpV9FfivNsYtK2bw6jXNLQf4jY5gBqOk3f8np3qrG535rusKaYHgBGP9KBcv3mzxPxR/1foppWLw+lnHmsFj3DzpMnc36k3BMxT4nYJp4r36Qq5TYMnCXidotYkGkjaa8UuNscXG3CzW3xb4s4siMLY8NvjRJxwmOdqaZT9OOU67tOiiZNN0wAOJiVSrnZ30vHz9fuYEFd5FAW3ZpiR5sDqBXjfK9aheetNc+ymDS3QIodT+eepppeK6Ze8eNntWe3bdNZGwC6zJfn7ZKn+fy3UehKYWHz0Xyuh4SVEfHSHix4bT2Exz7NlftYWGmbT82cJ/MrAMROZOdVk+0DWay/+eRXIm47id3FUxJYwG8u0nDfLfWo5qONLJZd8ow8Nra5xRPhpu3zVm/ZQTlvb28RH/oiiWq6xUvxavzNPanGHNMAEOQrj41t4YqrnXNtwn/TbTcivDzVJLThRSj6LZOLCvj7+1JNRgZf/9/vMUbEoSX5vuFEDgvc/bzlGPb3ZjfqvMI8ynVaOFbEMzrxIgPmQiO2e7d7I+6nHF1ry/M2dWhzG+XMOdaT+RUAjp2Sc55tYQ6bgH/ndCleN12QG9ZrhN27dquoWFEURVEURVGUa0MfCBRFURRFURSlGKMPBIqiKIqiKIpSjGG3lj8ZyccPImJAW5Eze0BbNuV+9vrlGvCbGeY2lcqXpRKzFxgAMvNkb1yj2mw+0TmuOeXWr5amGCHVQqnmSJbshw4tyds0csG7lGs28mYRB/lw/17zqf0o54lRmK2HL3pCGxG/+SL35pp9lACwopfsX92TvpdqbL3H1W+QuoL7pnJ/+abBbKBi9jZOa8+93M27WgzNDFOeVS8lUMkh07wMbGQ1ahD3l/t6y/7OTYNmUY0nBlim+RVgN8Ba2W+UiJ/7+3SqWRU/hnJmn2bA4Ca8nfls/jKphtRRrJrDZlt9lrCxzMZjm0R80GIGZevFNTU1Qb6lqObMedYQmEY2VW+vQTVmL269UNaEfHuKdUaffZMo4u712AyurB+f29v2HBBxxXvDqcZmTLZughz7MT0epBqrPihY6m5MDQzAxj2Ave/dhAyxAHw74x0Rl7T0HkeVZiMr02zS1BQAQLMGNSk36U6p89k0jucI0wCrSkAVqtk9h43tPMETA6zxt46lGk+0Ry1m8XzeZDb3l5vzt63XOa+Arxem+eQ8y/loGwemSWa3R1tQjXkNBYC7qsmW6dHL2SisTDDrxEw2LX6bcvmu1OuZhnwAsGH4G5Sr21WalX47j6+9N414mnLmPclbO/i8shqaGf3rgaVY1zjl648od+S4PNds87Jt3vjxvNSABfrw/i3jW4ZybWfL88rUPgBsNAkAsbdI49W7KrO53ppucSKuMYo1GjtG8bluGlR6aupa0V/OsQ+3ZZ3Byg83Uo60R4PHUU3r8SMod9skqXn9Ln6hiPMt2ourRX8hUBRFURRFUZRijD4QKIqiKIqiKEoxRh8IFEVRFEVRFKUYow8EiqIoiqIoilKMKTJjMsdxBgG4DUBdABUAlARwHMCXAF5zXTfxF173VwB9AcQByAOwGUCC67r/LoJtSvStGBBXbVgzkd+7ZZ8sPMOijNg2dShnGqGkJR2lGtMoDGADI9O8CPDMwMgmWL6x4g0i7jeRBafItxzjEo6MS7Pg1GY6lJMjxUBBgSzITDl47IrvlZfH4rn9z/+Tckv2SsHXlrQ9VPPB+q2Uyzont/PeOxtSTePKkZQbVF8aHx3NPkw1Xx5dT7n8Qing7VqzG9V0/nQA5Za2lsK01Mx9VFOrpxSzRjXi8bO6BwvcKpeKEHHsaywcTRrGgrPAx6Wg3hQnAkBM59aUq3GPNEyh8wywnmvBjaRIa/uIxVRjM/Mzx9n+8e9TTZNJfBwevP0mEXtiXgSwgdHbM1jc2SxMzjVDNkymml37eUyZJkCbB7HA3rYPfjqTKWJThA8AHeewwD3nvDwOZYICqObASBacL9gjt+uzAzup5u5qtSjXL0EK001BHwAs2/cO5S4USnFnqwgWFXZbw99vVgspYozfyAsPnM7OplzDStKkrnudLlRjipj9u9anGuSyyH/aC9JUafTy5VTj58PmjLkX5FxpMyFMfp3HvnmOBtdnA0dPzrWUnQepJjyW3yv7vBShlvDivzeeOplOuTvvlnMzGXICV23KaRPnVgiQYz0tM5NqVq6Wtx/hldiAK/5BNqTqN9MQ/lqMpnKmfk05/w5SIB3ekI3YAgNZUP96O7nAxScpLGZNPMHi7rXt5XbaFoDoev9dlAv1l9f7sU1GUc3hrAOUM01OS5Xg+ebzI2yul35emvdlnOdj1bPuUyIesYmvhWu+YnPWrcPkXDbt+/lUM30ejx9zwZB28SwEXjtpGuVa9ewl4v3vrqWa6n35Gm2ea+Z5ljF7Owp/zPnDGZM9D6A1gNMAvgDwCYDzAP4K4DvHcegOwnGcyQAWAagD4HMAXwNoCWCD4zgPm/WKoiiKoiiKohQtRbns6EMAvnVdV/xp1nGcXgBmAnjLcZyqrntxLUTHcZoDGAjgJwBNXdfdeynfFBd/VVjgOM6XruvynxQURVEURVEURSkSiuwXAtd1vzIfBi7lZwHYB6AygNif/dPgS/9NuPwwcKn+PwBmAwgGwAv2KoqiKIqiKIpSZPxeouLLDZV5AOA4TkkAlxvrufnxv7kHfuPtUhRFURRFUZRiTZGJin/xAy6KhhcBSAZQy3XdQsdx6gPYBuCU67oVLK8JAJAFIN11Xbbn9PyzE33DAuNuGC6d5DwRB5uuxACQPGGFiGOeY5lD8t/YobLtvEEiLihgV0BTHGjD5kJoOnIuG/481XSawC6dPkHyvRJHs6Av5rF7KVfnYSk4/WETi3xtJM6Q+672MHZ+DI9kEbPpfrl/Lou2qz9reW7MlSK04Jr83jZnRJ8w6bwYYRGT2QS8Mb3aiTh51iqqqT2WXYgrVZDDu3RpFmkn7Tsi4gtpZ6nGJl4zx7B5zAHPjrt5zAHPjrt5zAH7cYefFPB6Kg4+dUC6bYZFh1HN8e0s4EVZuR883i8jO/J7mezNEGFIY3axtQlHze38I4xXc94CgNw8eV4dsiwgEBXFbsnre88RcfM5vajGNi+mfJMi4vB6EVSTlpjG29AgUsSlAvgYZ59jt9RcY7EDm5AzyRDLh9fm77vhOXZwp3kql4Wynhx385gDnh1385gDnh33Mxns2m0TB5vXx2aTe3j0Oi8/OU8VHuZroW2/ZJ6TovA9Y9kV2ObOvK63dJ+uPpiv46tGygUDhn7AIv/fe7weTmMn74jw8lesyTh8mnK00IjlfseTedGTewTg6q8Xj7wtBbtJey3z+Vm5QIJN8O7ny3OuiTlHAZ7NU+YxBzw77uYxBzw77uYx3zvuS+QezyoSUXFRaggAAI7jDAVQG0AAgFqX/v9RAJ1d1728J6te+u8RfgfAdd1zjuOcARDiOE6Q67pXvltWFEVRFEVRFOV/psgfCADci/+2AwHAYQBPuK777c9yl//Eweu+/ZdzAMpcqv3VBwLHcaxLmgKo/uubqiiKoiiKoijFmyLXELiu28J1XQdACIA7ACQB+NJxnJE/K7u8CP6v9Ss5v/JviqIoiqIoiqIUAb+HhsAHwH8ANARwi+u6Wx3HeRDAhwC2ua7LjlEXX5eOi78QlL7aliHHcRJR2jcObauKvNmDuWcM9x7a+tLNfsvwADYPab6UF0b6sstCEUdPaEM1NpOThVukycjOXWz44W30joeWCaIaq/lUmziZKM+9srbe2H3DpXmY/7M3UU3WzC38effL9raoFjWpZseAv/M2jGkl38eio+hwx82Um/LepyL2KsHPvkEB3K+fNkaahQR2a0Q1NhO3kBC53z0xGALYZOg3NRiy9Ht70q9v9uoDHvbrl+VjZetLNTURtv5LWw+oOV5WH2Z9SaMKfPxufOUJEWfn/L/2zju8qiJ/4+8EAoTei1TpIiJ2FCt2LIudRd0VQRBFOsQOKosogsJSRQUsLIKruKsrVqS4P7EDoiRACL0pnQRIyPn9cU/WzLwTciGh5b6f57nPzXzv99ycO2fOnDP3zjvvPsrZOewrirl8uOp9inV61TbA2vg0m+2U7d+aYhkb7XnavnnipT3zS7cls+mQi3c+6yLPXFwXn6nSGwutckKH0yhn5nPPUizx/UlWeX7XSZTTcnh7irlz+N35+4C/n3L7PN957BoMAWwydDQNhoDozLzcufpAdPP13bn6QHTz9Xd845nZ67leuLhtBQA+W8tmd6dVsttQqxGsF9romXf/dL97rHKb2nxebdvHJm43DHPMtHayWWI05lO+88olqmsvgJkTbQPDB98aSzmzu4+hGOlCPLqG+JplKbZ+iH19bPgM60t8fVeTYfZ90aj2XSmnz4yJFHO1Oe59BOC/L6Lz+C7WJ7jGmdGYZgJH1qD2aGpQ1wz/P2Rs2nPcGZN5CYIgA8DbiHzjn92aVofPrLjD/0TF5QFsl35ACCGEEEKII8fRWnb0t/A5Wx6dBGAfgCrGGN+gIPtXg0VHeseEEEIIIYSIZY7WgOCS8HkFAARBkA4g+/eoWz352bEPjvB+CSGEEEIIEdMUyIDAGHORMeYOY0xRJx5vjHkIwN0A0hGZOpRN9qS5x40xjXJscz6ArgB2AuDFf4UQQgghhBAFRkEtO9oAwCQAvxljvgfwO4DKAE4DUAPAXgD3BEHwPyVbEASfGWNGAugJ4CdjzKcAigG4EpGByp1BEHgcNQ6NhifVxn8cMbBrpvGnN/tH9V6ugMdnpLFg3mKKVU9qY5V9wt97m7KQ6qRStnBzWDEWnGxYb5vWVK5cjnLu/rgfxZZMt398qV+2MeWk7mIB3zPfOCZnjqkUALR46RaKob79mZf0YUFmQncW/o164D6r/MS0tynnRY+5zq9jbcHpKV1ZwLNx6te8D7fbupwlr3Cdv53MsUfOTrTKKTuTKScrOECxA04sI4uFx88NtsXBFUqwSKxep2soRmxlEeOKnSsoVswR8PqETk0HssFY/VYNrXLK4lWUk7Ezb1O1zb/voBSf8dL6NFsYe+vjT1KOz3ipaiX7HPGJihPuPp1irkiyeJHilOOK3qs/2YZyBt3JP4qmbLMNBh899wHKScvcQ7GG5Wyx3BvJkymnyxgWKBIekWj9ujUoRvXiEeK1e/Jxin0y5EWrPGMF950+mjWwhZufdWZh5apdqRQr3d7ez8UTWTxfNI6F6r9O4LbusvgNO2f0Qs/3Vh5RocuPia9TrF5vFiOnj//eKie0bUI5PgO8+AS7fXpF6cXTKTblPlvE2G65R1DrEXK7xkunjuCFMg7HeAkAvpr4MsXchT/aj7uZcs6ofC7FALuf8C2QMOXnz6yyK1wF/H11nLH7sn7zB/K/b8j9tysi3p3GpnmpnnbuLj7g9m0Am5cCLOD3CYhbjubr+Ct32W3jjgkszF8/6HOKuST05OPy6+CpFCsSZ59HPpG/Wy/p/2ITtA4f9aLYshRHqO7pA93+BwC+Wehc2/fxdd0Xa9zFPrc/emEE5dwwme/V3OvTGc3t1fQ3F/sO3BIPj4IaEMwBMASRqUEtEBkM7AeQCuAdAKOCIKC7yyAIehljfgLQHZGBQAaAzwEMDoJgfgHtmxBCCCGEECIXCmRAEATBSgCP5Zno33YygMkFsR9CCCGEEEKIQ+NoiYqFEEIIIYQQxyEaEAghhBBCCBHDHHGn4mOJMWZJmdrlm10x9jYr3vMsW9R3aWL3qN6v9322SOrFiSyM9YnJUofZeQPmDqecZy9k0UvbSb2tsuuQBwDr1jpOpXsyKccV9AHAVUNtEaxPQLht526O/bLRKqdOYZfOendeSbFyzW3h1o7l7H6bPpUF2a6ArkqrOpQzt/c4irWbkkgxl6Rl7Nbq1oOvDrxiwDsut8o1L6hPOYNv7UCx9g3vssrdZz9MOa7AdNXuVMoZ/xOLZ5+/uK+9j/1Z5FezVlWKueJALxVZUFunlu1w+vH93O72HWCx3Bdr51rlr9exmH36BHY4/WSMLTC9bdwzlLNjK4uYqzsC5Qeu5fbavjELFF0B+HUT+1LOF91scWC9h1nM7nMTTR/9nVX2CeybNGVndHLN9B27oobf6yxbmJaezuLgAwdYGLdhi73OQ8pgdhdvPfI+il1zXgur/K9531POW/c9SrGr/mYv+BBNHfj+36wFbGlTpAgviLD68ySr3CmR20HiObY7q69NlynGwlG3XgbefDvl9HiNBcr/6vm0Ve44ZRjl+ESorjh3cNu7KafHtAkUS0iwndg/7sRCTt8xdvG50fqExik/ptoBz/nhuhID7Ez8yzYWkyZOZQf35zrY9dBlEF+PXXfflGe4nbv9AcDu8KnrWNCbtYEXB3Bdj30LK9Svy+JnV2R/xSsPUo6P5/7U0Sr7FgKI8zjN7xluL8SxKZ37G7cOAKB2XfvaMGf2D7xTnnuX1LG2+3zydl6s49tNP1nlK+tcQjmVivOiFO4iDad14/PRd50rV9FuGz5Btm9RCpSzFzFw3wcA3ntwEMVqlLQdzm98ze4TVz3/FfafKE7FQgghhBBCiOMXDQiEEEIIIYSIYTQgEEIIIYQQIoYpKB+C45aKCWXx0Jn2PNCu0+25ze58WgAYd1tPirmmI9ObfEs5b93L82BTd620yve3bEc5DfryXOMK1ctb5aldeH75tf1soxDfnLerOnalmJuXcoDnAvrmuKVPX2KVmwy7gXLqnM/1ubC3bSj29eavKMdnhDJzgj2/0zVwAYB5G9iyYpWjrXDn4QI89xAAyhQraZW372UNgW9eeJ2LGllldx4uALSodBrFvt9iz8n89LsllNO5hT0PtWLxipTz49KVFKt2tWMe5DEmmz2UjZ5cAxXvPMpypSmW1P/fVtk3D97XphKK23X1TpdBlPPUFJ6Xuind1rPM6vkcv3cRNpvZn2XPl28/+SnKOad6C4r1ene8VR5xG8+jDaaIYAAAIABJREFUrpbg1PkWnt/uM8D568f2eezqjoDoNCBxVfm9fXOWkxbYOo3Fo6dRjmt6BgAJHew2vP8Aaw/WLWJtzqvO+ehrBxfVuIxinW65wirv2s//79K6PHV24HT785T3tFcf89+w9UGZAc9rdk355j78EuWc1pH7su9f/YdVPuuReynH7fMB4JVF9nn1Vc+JlONrG65J3ovfsLnW2o2s5crKtOfwb0hbTzmzuvG8+92Zdl/ZYiT3k6/cybqbap3tufE+A8frXh5Asf797fe6sCefjz5DsfNe6GwHynJf7dLqJT5WPg3I+s22xmZWv2cpx9XFAKwBmdGDzeA2p/9Gsdq9rrPKvvZz5fk8n71l5TPsgEf7WKMKX2dcjZvvfDz7VL7+d2hmGzTOmfUd5VSoW4lia3fbfUmlErxPj02yz6vWj51DOWXieT/bjOxhlX1GYW6fD7D+ouHQtpTz8hO9Kebqg2Z0e4Jylm5bRrFuM0Za5QYn25qCDcXiwZ/u8NAvBEIIIYQQQsQwGhAIIYQQQggRw2hAIIQQQgghRAyjAYEQQgghhBAxTKE3JournNCsTBdbIOiaYn0/5k3atoRHjFi/bGOrnHD/WZRTs141irU+o6lVHn4JC6RW7Uql2IUPdrLKiye+QzlF4+IpFg2ZWRlW+bUlLCoccgGLLV1RoU+0dcW4HhRzRbauMAcA/jqRRT0LH7GNZXymJymrNlBsxRC7rloN70Q5N17Ex881MIrGvAgAXh9j11Xr6q0pp99c/ny/rLBFUzt2sAD06z62GMlXB79v30UxV7R0x4TBlJO+l+VI5cuUssorH2NTsElL2UDp05W2sdxldVmU2mPwaIqhiP29xMwhf6OUemXq8XYO143n88pn2LRj5e9Wucl5DSnnp+5sROSa8DR6kkWFi56cYpXrleH3nrdhNsVcfALbDh+xeeF778+zyj5RoXcxgiG2aNEn8v0hcTLFGnS3Bec1m5xEOWl7WbxeNM4+xls2b6OcSy47k2JkYBSFeRHABkauMBcAqpYqRbF1u+zz6L1Z/6Wcmo6xXeKNLOjtMZaFv247Tx/5DaUk3M4C6Zpn2mZspUvztemFdiyo/TDFbhtLNm2mnE9u4/0s1beVVS5TqiTlzO/LixG4Rl0b0rhfvrazxwS0mv15Zj7N/VS7RBbZLhlvn6NvJ79HOfeeehfF9mTYfaxPxOx+lvg4Fh5/kMr9YovKdp8XjSgVAK6ufb1Vdo8BwGJvAGhU317EYNkCNnXEdu7jm7RtbpW9pqdJLCZ3zzXXkBOIzpTTNeQE/Kacp1c72Sr3GMYmpMh07mE9Row+4bhrpJme7jEYLM1t373fcN8HAPbvz6DYikdto763lrHB6YJ1bK737hx78Zrde+z9zJiyFNi6V8ZkQgghhBBCiPyhAYEQQgghhBAxjAYEQgghhBBCxDAaEAghhBBCCBHDFHpR8SnNTmn2wyLbFW/acltEnJHFQrWral9JsU4f22KncVewiDFx3kiKbU1Ls8pn1qhBOZ2b30kxEjF3bEk52GeLn0Y9zqKtgdOnU6x4vC1G3pfBIphtG7dTLPkFW6zbuMO1lFOuJQsNj6Q4eMtKdtus3tB2v9y4kN1TUbEEheLL2LElA1lw3vixO/i9XJbtoFCFc2tRzD0Ovv0s19QWLbmiWACIr85OrLUd8eOsLuyo2rgbu2Ynj5tpla97tQ/l7NvP58xq5/jVdwRvADDngQkUG/R/9n5VSmAh11OtnqTYmt22O3NaJguySxZl4ehna7+wytv27qScHXtZpN31tHus8iPzuT4//sp2v/52AIuvR/30GsVGv2qLXqMVVn4yfJRVvqprN8pZ8Y9PKHYkxcHJQ2dQrPWILnluF1ec3VKz1tjHwT0XAGDXnjSKLX3Kdi/1LXQw+wEWxrqO8TMf44UV+r9rH9MDB1jsmfJdCsVqtqhtldctYXf4+mfUo1jJUnaftGYd93e1a1ahmJu3Y81WyiFBJkCutddffwGlnHsS72eflj2t8vo07su+XD+HdyHLvoZ1bMp9vE9QP/Va+/xL3cWC2lO6slty/bNt0auvXzyppH2smjx/I+UkDeAFNUrfZTsA+xbd8F0zG11ui5GPtDjYPca+c7bxQ1x3yX+3hdu+a4PvfPAteuHiOmsDwLrUTVZ52sOPUk77oUOssnsNB3K5jt96tVVuftMZlPPzfBb50nuP4bo7dcCfKeYuOONzdF8xkRdIaHD/DXZgn3Pt/XQdsCtDomIhhBBCCCFE/tCAQAghhBBCiBhGAwIhhBBCCCFimEKvIShWrVSzugNskyh3jls08z0BnvMZzXxPAEhzjCT2eUwrfGYzSc48wpqn8pzsuQ/Zxic03wzgOWc4Puel++ZNuseheDE2YlvUi02kZq2x5+KdXfVsyjn92bsplpZuz5veOewryvHx4ar3rXKnV1lLsvHpLyhWtr/dNjM27qYc9ziU9rSxbclsOuTibdOeeYxEEf7eIP2NhRRzTetmPvcs5SS+P4liKas2WuVo5nsCPOczmvmeAM/5vPl1npuftMxTLzvtOby+efe+9uni01G0mWDP/T9e56X//N6PdqAK91s+3Pby2Vo2dTqt0mkUazXCnk++0fP5nu53D8Xa1LbPq237WA91wzDWpbjHOBoth++88uHOOS/dthnlzPSYMz741lirPLs7ax98fS6cNhRfk83n1g/5iGINn/G8l0M01wv3WgFEd71wrxUAcOpTbGRVo2pFq1y2LGuPkpavpVjGOkcz5Onf3Dn2x+u8dNeoz3fNXjroHxRz7xN8dV6zVF2KtZl6r1X+8s7JlNNwaFuKueZ9kxfMo5zFv6ykWBHn2FQqX4ZyojmvfP2Uez+1/OH/UI7PfHb32AX2/7uep+7Xv6Ipxdz7lJqDrqIcn47i9ovPscovvu2cs1OXA9v2SUMghBBCCCGEyB8aEAghhBBCCBHDaEAghBBCCCFEDKMBgRBCCCGEEDFMoRcVNzmlcbP5P9hmKC2Ht7fK0Qh6ARaheI1JOrF41RWmRWMwBLDJUGE3GDraQjWfsNkVFftEmj5BrSuSvP9NPp670/ZSbMDNtrgrZdsmynn0XNvEzWfA1bDcKRR7I3myVe4yZizlYAsb2bgCrPp12Ugv5cdU3u535/NV4/PqkyEvUuyiGpdZ5SbDWBg/qn1XivWZMdEq+8T6PqGYK3qLxmAIYJOhWDQYcoXN0Sy+ALCw2bf4QjTC5vfvGkY5voUU3PPdJ5As1asVxao7QtXzz2Rx4HMX2QZcGVnc7uIMf9c28kdbUD9++seUU7NWVYq5/caMbk9QznUjHqdY1UrlrLJr8gSwWRLA50ypvlxPZUqxgHfdIPv65LsWomwxClWoYAtFXbNGIDrjTNc0E4jOONM1zQTYODMa00yAjTOjMc0EPIaUUZhmAixsjmbxBaDghM3lqpajHJ/w1xXUuot+AMCw+e9RbMN6+56gcmX+f3Wr2/cEg1uz6alr8gqwkd0bv7KB65C3+L7BvR6mpHjuEUZ/R7GE7vb5MOqB+yjniWlvU8y9L/p1rF2X159/E1YsTZGoWAghhBBCCJE/NCAQQgghhBAihtGAQAghhBBCiBhGAwIhhBBCCCFiGFZ/FgDGmIoAlgKoAiApCAJWZv2R+xcA3QE0A7AfwNcABgdB8N+C2Jed+3dixgoWx+SkWQMWxn3Wmd0gV+1Ktcql259OOYsnstCoaJwtkvp1AotnfCx+w84bvfBVTiqV9yH8MfF1itXrbYuR08d/TzkJbZtQrMK5taxyfEJxyvE66Ra3RZJT7mMRY8qO1RT7ep0t/Jk+gR1OU/+cSrFyJ1eyyo0fvo1yqnsEyg9ce6VVbt/9Zv5/u1go2nP6OKv8Vc+JlFPvYRZ3PvbKW1Y5GjFSk6YskPSKUF1xZ1FDOU0uYLFVerotevWJdeOqsmA45WVbjNh6JIum3l7KQsqH/jnaKr9yF7eNOyawY+z6QZ9TzCWh57kU+3XwVKtcJI7PIZ/IP9U5/9P/xcK8Dh/1ssrLPIIzn2um2wd9szCZt9t3IM9Y4y43UspHL7D77Q2T+1llV0wPAGc0b0CxL7rZwnTfMfY5qi/pYzt5nzriT5TjW1Rgx3JblPnWOdyXzx/Bzs9frrcXkkicysLRlx9k8WGXQcOt8gfbd1HOqMvs41csYKGsK0oFgNR1jqh3K9c5anHIPTbu+QIAKc+wW/sVrzxolZs0r0c5z/2pI8USOra0A552t3Hq17zd7bamcckrfJ17O5ljj5ydaJVTdnLbzwp4Hw44MZ+4+7nBfBwqlLAdm+t1uoZyCM+xWrFzBcWKOU7lrngfAJoOZMfh+q0aWuWUxasoJ2PnToolzhtplb98/TXKuTSxO8Xca0Hv+/h8PLXn7bydc7/hE2QPmDucYpvS7QURHvs335N4r2FrN1vl1b+wg/xQZ6GKU59gV2vfwhjbdu62y79spJzUKbyQS7077XuEcs1ZJJ7QgV3X06cutnM891dVWtWhmCsibjfFPl/WbLfrKD8cqV8IRgDguy0HY8wIAFMANAfwGYBvAFwJYK4xhu+ehBBCCCGEEAVKgQ8IjDGXA/grAP6K1M5rA6A3gN8BnB4EQbsgCK4BcDGAAwAmGWMqFPT+CSGEEEIIIf6gQAcExpgEAOMB/ALghTzS+4bPg4MgWJYdDILg/8L3KAfg3oLcPyGEEEIIIYRNgRqTGWOGAhgA4FIAqwGshEdDYIwpAWA7gOIAagdBsNZ5/SIAcwHMCYLg0nzsz5IiVRKaVexmG3O8dd+jVvmqv/WnbaOZp33NeS0oZ9aCRRQrUqSIVV79eRLldErkueqJ59hmTPsOsLFVmWL2fEjfnN6BN/NcwB6v2XqEf/V8mnI6TmETINckxzUOAoDBbe/m/zfNnuebkMDzbnfsYMOtd7oMssqVSvBMtE3pPPeveBFb25BQhOdt789ig6j2k5+yymPa8/zLXu+Op5g7F/fq2tdTjm9eoTuf/Pa2F1LK8xf3tcr1+vN8T5+h0YYtW61y1gauXxTh7wQWj55mlX2mZ77PQsZdnvnsqMiaE9fIbs9wnp+8KZ3n4rvztGvXZZOlObN/4H3Yk2kVU8eySU7ydp7H/O2mn6zylXUuoZxKxe326TORO62bZ26uUy/lKpallI1Pf0GxhLsdHVM5NnXyvdd7Dw6yyjVKsqHhja9xv/j6XXbfWbpoacrZnbmbYn95c4hVntC+N+VUS+C5uO7c8eteHkA5Sf3/TTG3fbptEwDOe6EzxVyzK58ZlGv4FU3/CnAf67vu+I6Vq7fanP4b5XQZ8XeKVahe3ipfeT5r3ty+BeD+xXctTFrGc7ndedruHG0gFz3bHZdb5ZoX1Kecwbd2oFj7hvZc8e6zH6Yc19QRAFbtTrXK439i86nD7XN9pnyEpw+sU8vuuz6+nw0cfdf/rfvsPr7bjJGU42Pcbba5ns9I787XhlDsrXsfpZhLVsCGhm0G2ue72zYBYGoXPn7X9nP0ZJ66w/Kdeed4Yu655utffSaZLgt7s5nY15u/oph73+DT7zz4FpuHuv2L27fsm/QLgt/3Hl/GZMaYFoh86z8pCIK5eaQ3RWQwsMUdDIRkX8X5jlsIIYQQQghRYBTIKkPGmDhENAPbEfmFIC+ypdS+wQCCINhjjNkOoIIxpkwQBLzUg/3/l+TyEi+TIYQQQgghhPgfBfULwUMAzgXQPwgCXjuOyf6dOe0gOdm/tfNv0kIIIYQQQogCId+/EBhjagMYjMh8/8nRbhY+H0zAwIum50Juc6fCXw6aRfs+QgghhBBCxBoFMWVoLIBiALodwjbZU4BKHSSnZPjMyqRDIAiA/Zm2MO2iGpdZ5U63XEHb7drPgtNL69rjjoHTp1FO+XJ5/6Ax/w0WVmUGmRRzDUzmPvwS5ZzW8Rar/P2r/6Ccsx7hxZpcUc8ri1iY5zXXcsRVpUuy6O7Fb1jAt3ajbTCUlcnCI5/5y297bQFd6Xiu3/LFWKB03Xh75porhgb8RkhNzrMNYi496UrK+bgTjzEbPWkLfxY9yV58rjEJAMzbMJtiLtUSbKOnm65j4fF778+jmHuMp/Z9hnKuHfIIxS4cbhsa/ZA4mXeqeBEKXTba3q5CYxbdFY3jHyVdMx+fONB3Pp59qj0jsEOzNpQzZxYbvVWoa5vWrd3NAslKJSpS7LFJ9rnV+rFzKKdMvL2fbUb2oByfUVg0grOGQ9tS7OUnbLGeT8w6o9sTFFu6bZlV9okRG5zMQuNrRtqmOPP7soGjT8A/6jZb3NmmIy9+gGq83cynbUO61T+mUo7PyOrJPrbgtFgRXsRgfp9xFHNFzK75FQDEx9nv9UEqmyW+1+NJirmGYjMTB1GObzGCUn1b2fvo6TsbncKGRssWOKaO37B4fuEyNsByxbJ/v4UXVnAF9gBQplhJq7x9L1+6feaMdS5qZJV9C060qMSLGHy/xV584NPveOZw5xabKFaxuH1u/7h0JeVUu9ox1/Ncm2YP5bZPCyn4xKyeewRXGO+aUQJ+wbmLa+QHAN+PeZNiJZxztH5ZNqhcl8p15wqNW5/B17nhl/Cs8fnP2HV14YOdKKdWKXbli9bENSeZHoO615bwvdqQC+wFRKJZKAMArhhn9+mtxvMiKr7+e+PmbVa5ZeUzKKd4MV4UossYW2i8YohtfnvNB9dj2e9sknc4FMSA4HpEtAPjjLG+1M++U6xjjPkyOzcIgt2IrEAEeH0ZAWNMKQDlAWzPSz8ghBBCCCGEOHwKRFSMyM07r8EXISHHa9n/LwnAPgBVjDG1PCsNnRk+8xqeQgghhBBCiAIj36LiIAiM7wHg5DAlKUd8e7hNOoDsRV9v9bxtduyD/O6fEEIIIYQQIncK1Kn4EMmeSPu4MeZ/kwiNMecD6ApgJwCeECuEEEIIIYQoMArUqdh6Y2PqIRen4hw5LwHoicjyo58iIk6+EpGByu1BEPwzn/uwBBWKNcMdtvjwksvOtMrRuJkC7GjqczP1iXOrlrK10+t2sSzivVn/pVjNGrbraeKN7JbYY6wj/PU4z6aP/IZiCbfbAumaZ7IbZenSLPJ7oZ0tBvwwhcWsSzZtptgnt9n76QrlAKDj9ZdSrFKCLVR7qhWL9dbsZlGY6xBbsijr1z9by86E2/baroc79vKx6nraPRR7ZL4t+P74KxbdfTuAx7ejfnrNKo9+lduPK6xsl8hC4E+Gj6LYVV1tnf+Kf3xCOQ26s5twzSa2mDRtLwvqfOLgLY5oKnnoDMppPaILb7fSFsL5nINdN1OAHU2jcTMFWLR8erWTKafHMBacItPpK4t6FkIrawsiXQdSAEhP9ziOl7bbecqqDZTje6/9+20B3YpH/0M5by3jRQwWrFtqld+d8y3l7N7D+3n1JXbfee5J9SinT8ueFFufZgu3v1w/h3Iys1jA27GpLT7s8FEvypl6LS+2kLrLFtSe0pXFrPXPZkfcWV3s9zqpZG3KafK8fc4kDWDhYem7WDBITt4drqWcRpezK7grDsZ2Ftg3aducYrt3p1vldUnrKQeleNawe976ztkbLzqLYrMW2DN8ixThhQdWf55EsdfH2OLO1tVbU06/uSzE/2WF3aZ8Tvdf9+E+13U4/3079/GuEP+OCYMpJ30vH4fyZezrzMrHWHA+aSnv06cr7QUnLqvL7aDH4NEUcxeqmLacBcQZWXwvc1Vte7GMTh/z5xt3BYuDE+fZiw9sTeOV48+sUYNinZvfaZV9IuaEji0phn12nzDqcRa4D5w+3SoXj2dh7r4MFhq7ruTJL7xDOb5ztFxL+/q48JE3KMdtYwD36a44GABaDWextXt9rN7QdnT/bfT3yNySdnw5FR8OQRD0AtARwK+IDAQuAPA5gEvyOxgQQgghhBBC5E1BiYqJIAhSEYWXQOhdMPlI7YcQQgghhBAid47pLwRCCCGEEEKIY8sR0xAcD+SmIYgrbv8wkrWG5xCWa8rzdXftsefLLX2KTcBc0woAmP2AbcrRoC/PZ5352FMU6/+uPdfwwAE2pEn5LsUq12zBc17XLVlHsfpn1LPKJUuxwdiadWxyUrtmlTxzdqzZSjGaf+2ZuxpfhvdhyUB7TmTjW6+mnOY38Xzdn+cvpRi99xie437z6/b8/KRlbFqFnTx31J137zMY8THngQlWuc0E9vdzj7t7zIHojrt7zIHojrt7zAHg5/d+pBiqsObEJf2NhRRz544m/53NaK57tQ/F3HrxzQX24Zrp+Qx4pj38KMXaD7VNeY6H9nrqANu8sGY97rfWLeI2vGKirdNocP8N/A/38dxjt1/0mfvFV2fjpdqOHsqdqw8Ajbu1o1jyuJlW+dSnWBNSoyqbyJUta2sykpa7K1sDGet2Uow0WFH0U+4xB6I77tEcc4CPu3vMAXg1b+5xWDqIr1e+4+7WeeN72SwNFbntR1Uvj93B7+WybAeFKpzLlkXuXPGNC7md+67jbps9ku3V12/t28/HarUzv7x+/ZqU414rAL5eRHOPAPD1Ipp7BICvF2kendG+/Txf39UjJrm6GAA1T+XPPPch27Axmn4qmmMO8HF3jzkQ3XF3jzngP+6uFsh3zfbdNyzqZc+en7XG7rt7XdMfa5etO/E1BEIIIYQQQohjiwYEQgghhBBCxDAaEAghhBBCCBHDaEAghBBCCCFEDFPoRcW1G9VqNvZT20zjtEqnWeVWI9gMYqNHZPN0v3uscpvabKCybd92it0wzDHT8ohSXfMpgA2ofCIUF69JTttm/P8m2kYvD741lnJmdx9DMRJSeURM8TXLUmz9kI+scsNnWJC18Wk2CmsyzBYRjWrflXL6zJhIMVfYtPxhNmxqOLQtxdz6i8ZgCGADk6gMhgAyGTqSBkONH2IxezQC3iMtVFvc296HNlPvpZwv75xMMff4+Yz7Ji9g47zFv9hGdkU8Zn6VypehGLUNz3nlCqt9QjlfW0y43zZ62j12AeWUvp41Y/WvsD0fXQEaANQcdBW/lyOsvv3icyjnxbc/olhcUbuuypQqSTnrBrEBXulOZ9sBx8ANACpU4Dp3haPRGAwBbDIUjcEQwCZDR9NgCPALY10BbzRidoCFzYcrZk99mdvr6c/eTbG0dNvAcOewr/J8bwD4cNX7VrnTqyMpx3dtKNvfvv5mbNxNOT7BcGlHGLstmY00XbyLNnjE+oTPKNS3sEIH+55k5nPPUk7i+5MoNr+rHWs5vD3l+AxGXVGvr5/y3ks453E09y0AG2e6pplAdMaZ7uIdABtnRmOaCURnwOfb7nAXpTkcMTvAwma6B/twNbBzv0TFQgghhBBCiPyhAYEQQgghhBAxjAYEQgghhBBCxDAaEAghhBBCCBHDsBKxkLF513Y88qEtvInGifWriS9TzHXJaz/uZso5o/K5nr2wRcU+MdmUnz+jmCtezchiQV2cscd0/eYP5H/fkEW+roh4dxo7DqbuSqWYK4SpWqkc5ficX12xk08k1nL0LRR75S5b4HrHBBYxrR/0OcVcEnrycfl18FSKFYmzTwlXDAX46yX9X7Y4r8NHvShnWQqLbF0RarMGLF77ZmGyHdh3gN/HE2vcxRZkffTCCMq5YXI/irniwDOaN6CcL7qxCL31yPussk+otqTP+xRL2Wl/vgXzFlNO9aQ2FHOFv/c2ZSHnSaX4XBtWzBYxb1jPLpaVK3O7vvtju66WTP+AcuqXbWyVU3exkPyZb4ZQDMWLWMUWL/G5gPosunXrM6H72ZQz6oH7KPbEtLet8oset81fx7JA+ZSutjB949SvKSfhdta2LXnFrvO3k1nM/sjZiRRz20ZWwO38gCfm9pXPDWZxcIUS3C/W63QNxYit9vmxYucKSinmcRx1BfxNB7LjcP1WDSmWsniVVc7YyQ7LifNYiPvl669Z5UsTu1MOihoK9b7PFufvP8CLYPj6fbffSLj7dMrxCWqLFylulV3BOwBUf5LP/0F33mqVU7bxdefRc/m4p2XuscoNy/ECEG8kT7bKXcZwf+fF6c/r161BKb56cReXaPfk45TyyZAXKTZjBbuXu/iuKZ91thcMWeW5ppVuz/u5eKItoC8ax+381wl8btP7vME5oxe+yomexTJcfkx83SrX630j5aSP/55iCW2bWGWfG3Z8QnGKkSi9eDrlTLmPnYpTdqy2yl+v42vD9AmzKJb651SrXO7kSlZ5V7F14GU/Dg/9QiCEEEIIIUQMowGBEEIIIYQQMYwGBEIIIYQQQsQwhd6YLL5aqWa1+55vxVN+TLUTPcZLrgkZwEZkv2xjU5fEqW9Q7LkOtolLl0HDKcdn5pXyjD2H1zdX1jXOSV3H8yizNuyhmGu0svn3HZRTvy7Pv3bnHl7xyoOU4+O5P3W0yr45knEVee7onuH2HOVN6TwP32ceVLuubQwyZ/YPvFN7MimUOvZDq5y8PZlyvt30E8WurHOJVa5UnA1G3LmrAHBat9vtQEWes1iuot02fPoL77zUcvb8Tvd9AOC9BwdRrEZJ2/zlxtf6U87rdz1KsdJFbX3J7kw2CvrLmzx/ftlPtlGYb95o6jDWHgyYa59Hz17Iuo22k3pTjIze1nqMiTxtw53De9VQnvPuzhnetpPrYNsvGymWOsU25al355WUU645n487ltt6qPSprL9w58oCQJVWdazy3N7jKKfdFP58LknL2JzJN2/arQd33i8A1LvjcorVvKC+VR58awfKad/wLop1n/2wVfbNJV+1O5Vi43+ytRTPX9yX97O/Pce+Zq2qlOMz5SM853qdWmxo9PH9drvbd4D1Xlv3baVYtxmsK3AZd1tPirm6tEuf5vOqusdA6YFr7TbbvjFr7HzXsOsm2nXs0yfVe5hNFd3rdvro7yjFp6lp0rSuVXb7A8Bz/DxaiyZnsbYqPd3WAhw4wJ93wxY+VimD7Wu9q8cCgGvOa0EtGvnAAAAYK0lEQVSxf82z58a/dR/3y1f9jfvvaOrA9/9mLVhklYsUKUI5qz9PolinRLstJJ7DBqO+dl2mmH3N8tXLwJvta2iP11iL8K+eT1Os45RhVtmno/TpSwe3te/nekybQDkJCWy8uGOHff1/p8sgyqlUgs+rTen29cLV3HS4+B6sTEqVMZkQQgghhBAif2hAIIQQQgghRAyjAYEQQgghhBAxjAYEQgghhBBCxDCF3pjspHKV8MqdtmipWmdbnOczu7nu5QEU69/ffp8Le7LAxTUTA4DzXuhsB8qy4MRHq5futcqueAYA1m+2BUqz+j1LOT5RkSugmdHjEcrZnP4bxWr3us4qV6hennKuPJ8Fri0rn2EHPMLRGlUqUswVB+7azyY5Z5/K4q4OzWwjmzmzWHBWoW4liq3dbYskK5XgfXps0j8o1vqxc6xymXjezzYje1DMNQvr9e54ynEF2Q2HtqWcl59g8awrrprR7QnKWbptGcVcMWKDk0+inGtGsuB0fl9bcJ5QJIFyRt3G4s7O6bZo8q17WRiXumslxe5v2c7ez74sPPS1z6ld7DZ1bT82kfEJPq/q2DXPnJQDthjRJ+ROn76EYk2G2aaHdc7nNr2w99sU+3rzV1bZZ+43cwIvYuAaE87bMJ9yVnnE1q44zyewL1OsJMW277VFxT6RaJ2LGlHMFee1qHQa5Xy/hc3RPv3OruPOLXixhYrF+dz+candzqpdzeZ6rjHZ7KFjKMU1BQz/oVUsV640pST1/zfFXGGsr035cAXn3495k3JKeM5R11zvp8GTKWd/Fvdv7Sc/ZZXPqc6iVF//NuI2+zpaLcFT51tY9OqagP31Yz6PfYsRRCMKj6tqv7dvYY6kBWwstXj0NKvsMz1L6MBt2DV/W7eIxfqves5Hty1cVOMyyul0yxUUc6+jl9ZlPerA6dMoVt7TZl3mv8ELBmQG9iINPlO+uQ+/RLHTOtr92fev8rX3rEfs+yRfn//KIj6vvuo50Sq77QLwm+S9+I19j7d24xbKycr0WIU5/cZve/n+qnQ812/5YvbnuW68fW+6aZtnUYzDRL8QCCGEEEIIEcNoQCCEEEIIIUQMowGBEEIIIYQQMYwGBEIIIYQQQsQwhd6pGKWKNkNrx+Gzmi0Ymvn0YNq2XSKLbJeMt90E305+j3LuPZVdM/dk2IIkn4jZ5+AYH2cL6j5InUU5LSrboqVoRKkAcHXt661yqb6tKMcnjGlU3xZ8LfMIq7CdBWdN2ja3yl53yKT1FHOdg6NxMwXY0TQaN1MAOL3ayVa5xzB2cEWm55xxnSw9wnGfC2l6ui3uLlOaBZkpqzbk+T7792dQbMWj/7HKby1jsdeCdey2/e6cb63y7j3s4Hj1JWdS7NyT6lnlPi3ZBXV9GovlGve71SrXrMefr/UZTSk2/BJbXLVqVyrlXPhgJ4otnviOVS4aF0850ZCZxXX+2hJbiDfkgqcoxycqdBcjuGIcC9B97pfuuf3XiSMoZ+Ej7J7uunu7bQwAVgx5h2Kthtv1eeNFZ1GO62YKsKOpz8309TFcV62r2+7w/eby5/tlBbcp1xX06z7sXupzOP99+y6r7BPi3zHBvl6k7+X+rnyZUhRb+Zjdf09ayvv06Up2mr6srt3H9xg8mnJ8DtXTltsi4owsdt++qjY7Ynf62P583/3Ax2rHyt8p1uS8hlb5p+7/pByf03yjJ+3FMhY9OYVy6pVpSLF5G2ZTzMUnsu3wke28/N778yjHFaa6CxEAwLVD+B7BFfn+kDiZchp0Z8F5zSb2wg1pe/dRTtE4/v52y+ZtVvmSy7hfnjP7B4q5TuzudRYAkrcnU8wV51Ytxe183a5dFHtv1n+tck2P03XijSzq7THWFv6iCNdB+shvrHLC7SyQrnlmXYqVLm3fB77QjheJ+TCF28aSTbaI95PbJlKO736q4/WXWuVKCXytf6rVkxRbs9te6CAt0+7bbm7dHilJK+VULIQQQgghhMgfGhAIIYQQQggRw2hAIIQQQgghRAxT6DUENRpUb/bUv+15oJlZ9nz9jk15nrE7zxAApl5rG2ek7uL586d0ZcOd+mfbc9xndWEDjpNK1qZYk+ftuYZJA9j0rPRdtuGXzxitcYdrKdbocnte6pHWArhGZMlDZ/B+PsR1l/x3W6dx3atsPnPgAGsd3LnAPnymI+tSbQOjaQ+zSVb7oUMoFl/Gfq8lA9kEqPGtV1Os+U328ft5Ps/pd1kyhuvu1AFs9OLOxfeZ3ayYyHNHG9xvm2RhH889LteU5/m784rjq7PJSm3P3FH3fEicN5JytqalUezMGjWscufmd1KOa7IEAAkdW9qBfazfGfV4d4oNnD7dKhePZ+3BvgxbV7Bt43bKSX6B5+a752i5lmwGdyS1AFtWsrlO9YbVKbZxodOGKvI55J4LAJ8PjR+7g3K8LNthFSucW4tSfMfB3c9o2ivAbTaa9tq4WzvKSR43k2Ju37VvP59Xqz3Hr76j25rzwATKaTOhG8XcfjHluxTKqdmCrzvrltjz/H2f5bO1X1Bs296dVnnHXu6Du552D8UemW/X58dfsdndtwNYbzHqp9es8uhX2XwqGn3gJ8NHUc5VXe36XPGPTyjnSGoBfNfH1iO65LldXHE2/Mxaw8fBPR927eH+delTbALmaptmP8CmfD6DyJmP2fqg/u/y8fRdx902G017rX9GPcopWYr7pDXr7D6vds0qeeYAwI41thmsV1PoMV49YvcIH64Gdu6XhkAIIYQQQgiRPzQgEEIIIYQQIobRgEAIIYQQQogYprBrCHYWjS9apkodngeak/LFK1Bs7S6ey1mrjD1neX8Wzw9csZ7nacc764fXrcBzc4sange7/PfVVrlhpTqUs3TdCjvnJM5ZvnYVxYqVKm6V96ezXgAHuG0Uc+bBZWXxvL9Mz5xzd+jZsBrPBVy+geuuYQ07b/W2jZTja8G++Yi0S3GGYpnOvN5alXle4drfeF4hnHmhDavWpJTla/g4FHfqc1+a5zg4NKjB86hXbFpLsaLF7HmMmXt53fxGnvayzG3Dnj7CO1d1vzMXvyh/3xAfX4Ri7vmwaQ/P7T7g2YcSRe19qFC8HOUUK1KcYr8654zv81WvUpFim3fYc6TjDLefLOe9sjJZn9CwuqftO+doXAnuDxpU5jaVus3upzI889IbVeP2kvK7rfM54B47cPsBPG2oCNeBey4AfD4s97RXL85+xSVwvfiOg7ufUbVXgNpsNO11uafPb3gSH2O37/JdejMy+ByNL2Z/5pMrsL4kdRvrtty3z/D08UU97Sxzr92GfJ/F9dYBgAOB3eceyOL6rViiPMU2pdlzsnense9J/cr8mbfutfU5W7fxXPnaVatSbM0mWydWt3oNylm13q7PRrV4HftlnutVUaedZWXxQfY0Vxxw+gnf9XHl73yM3e28b57B10L3fPBdxxtW5X5j1Va7DderyPcyyzZyvdSuYh+HTTu3UY7vOu622Wjaa3yUfUSGU3fxRflcd3MAICvDifl23PdV+5G6R9idAWQFu4IgsE0wDoPCPiDYCKAkgOw78hUHSRcFS4PwWXV+9FCdH31U50cf1fnRR3V+9FGdH31OxDqvDSAtCAIenR0ihXpAkI0xZgkAFIQKW0SH6vzoozo/+qjOjz6q86OP6vzoozo/+sR6nUtDIIQQQgghRAyjAYEQQgghhBAxjAYEQgghhBBCxDAaEAghhBBCCBHDaEAghBBCCCFEDBMTqwwJIYQQQggh/OgXAiGEEEIIIWIYDQiEEEIIIYSIYTQgEEIIIYQQIobRgEAIIYQQQogYRgMCIYQQQgghYhgNCIQQQgghhIhhNCAQQgghhBAihtGAQAghhBBCiBimUA8IjDEljDFPGWOSjTF7jTHrjTGvGWNqHet9O1ExxpQ0xrQzxrxqjFlkjNlpjNljjFlojHnSGFP6INv+xRjzjTFmtzFmqzHmP8aYC47m/hcGjDEVjTGbjTGBMWZpHrmq83xijKlujHkx7EfSw3r83hjzfC751xtj5hhjdoTnxxxjzPVHe79PVIwxrYwx/zTGbDTGZIT1/bkx5tZc8uOMMb2MMYvD47PFGDPDGNPsaO/78Yox5ixjzMPGmHeNMevCvmNvFNsdcv9hjLkgzNsabveNMeavBfdpTgwOpc7DNnyRMeZ5Y8yCsH/fZ4xZYYwZb4w5OY//pTrH4bdz5z0+C7cLjDHVD5JX+Oo8CIJC+QBQAsBXAAIA6wG8DWBBWN4MoMGx3scT8QGgc1iHAYCfAUwHMAvAzjD2K4Cqnu1GhK+nAZgZbpMBIBPATcf6c51IDwCTAWSF9bn0IHmq8/zX9fkAtoX1uCTsR/4DIBVApie/R5ibAeCjsN7TwliPY/15jvcHgNsAHAjr61sA0wDMzREb6uQbADPC17YBeAfAl+H5kQbgvGP9mY6HR9gOA+exN49tDrn/AHBT+HpWeBzeyXH+jDjW9XC81jmAhjly1obbvhv+HYTX1wtV5wVX57lsf0+4Tfb1tXos1fkx34Ej2DCeDg/OfwGUzhHvE8bnHOt9PBEfAP4CYCyARk68BoAfwrqd6rzWJoz/lnM7RG629gHYDqDCsf5sJ8IDwOVhXU7AQQYEqvMCqeuTwk4+zXcDBOBcp9w4vGHaC+B8J/5b+FqjI7nPJ/IDQFFEvqwJANzhvHY+gPTwAtwgR/zeMD8ZQLUc8VvC+HIARY/1ZzvWDwCJAJ4CcD2AanndKB1O/wGgQhgPANycI14NwLIwftmxrovjsc4BNEBkwHWxEy8OYFK47SoA8arzgqlzz7ZVwvb+MSJf+HgHBIW5zo/5DhyhRhGPP0ZrZ3heXxi+dtax3tfC9AgvFkF4Q1QsR/zDMN7Ls83I8LW+x3r/j/cHgISww1kCoBEOPiBQnee/vl8P66l7lPljwvyXPK/1Dl/7+7H+XMfrA0DzsI5+zeX17G//bs8RWxLG2nny3w9fu+VYf7bj7ZHXjdLh9B8A+ofxmZ5tbgpf+/ex/uzHa50fZLsSOW5AL1GdH5k6B/AWIl86NMhjQFBo67ywagguBFAewIogCH70vP5O+HzD0dulmGBh+FwcQCUgouNA5Ftt4I96z4mORfQMRKSz6obIt81eVOf5xxhTAcDtAHYAeCXKzbJ1Ar46nxE+q85zZ1+UeVsBIJxX3QyRi/iHnjy188MgH/3Hwdr/h4h8UXRF+P4iSoIg2IvIL2BA5FfLnKjOCwBjzNUAOgD4WxAEK/JIL7R1XlgHBKeHzz/k8voPTp4oGOqHzxkIL9oAmiIyQNgSBMFazzbZx6LFEd63ExpjTAsAfQFMCoJgbh7pqvP80xqROpwPIMMYc6sx5iVjzBhjzEPGmGo5k40x5QHUCYv0JUR4HH4DUNcYU+4I7/uJSkr4aGqMuT3nC8aY8wFcDWAlIpoC4I/+++cgCHwDZPXzh8fh9h8tnNf/RxAE+xHRnJUA0KSA9jMmMMYUAVA3LG50Xlad5xNjTEkA4wEsBeBdKMKh0NZ5YR0QZF+YfZ1ZznidXF4Xh0fP8HlWEATZ3/Yd9FgEQbAH4XxUY0yZI7x/JyTGmDgAExGppwFRbKI6zz+nhs+bAMxD5Bv+ngAeADAKwApjzG058rPrfFtYvz7U7xyEIAgOICLq2wHgbWPMt8aYacaYOYgMzH4CcFV40QXUzx8pDrn/MMaUReRX+Vy3g47H4dIeQFUAWxDRRAJQnRcgzwCoB6Bbjr7FS2Gv88I6IMhe+jItl9f3OHkinxhj2gLohMivA0/keCmvYwHoeOTFQwDOBdA/CILfo8hXneefCuHzXxD5RqgTIqKzkxFZfaUUgDfDX24A1XmBEATBPACXIPJLwNkA7gBwMSJ19xkiK8Zlo37+yHA4bTlnHet4FBDGmNoAXgqLT+b4og1QnecbY8yZiHzRMyUIgi+j2KRQ13lhHRCY8DnI43VRABhjTgHwJiL12j8IgoU5Xw6fczsWOXOEQ3hBGIzIqliTo90sfFadHz5FwueiAPoEQfBaEAS/BUGQGgRBX0TmjxbDH7/YqM4LAGPMnxFZHno1gPMQuag2BvAPAI8D+MwYE5+dHj4frM7FoXM4bTmatq32fwgYY0oBeA9AZUQErOPdlGjepsB3rJAQTsXK/uW9X7SbFVDOcUlhHRDsCp9L5fJ6yfB591HYl0KNiZi8zULkG9URQRCMdFLyOhaAjsfBGIvIjWe3Q9hGdZ5/suswC8AUz+uvhc+XOvmq88PEGNMIkbreAuC6IAi+CYJgTxAEy4Ig6Arg34isZNYx3CSvOs+Oq74PjcNpy7s8r+W1jciFcND7TwBnITJdroMnTXWeP3oBOBPAgCAIfotym0Jd54V1QLA6fM7NkbiWkycOA2NMZQCfIjJXbhL8o+yDHovwW5DyALYHQbDLlxPjXI/IT5PjjDFfZj8QMWwCgDo54tk/UarO809q+LzR+Znefb1q+Jxd5xXC+vWhfufgtEdkyehZuegwpofPl4bP6uePDIfcfwRBsBMR7Ueu20HHIypCzdibiIjoFwK4IQiCdDdPdZ5vbkDkV7C/5ry2htfXbIfid8PYhUDhr/Oix3oHjhDZU1bOzOX17Piio7AvhZJQTPYRIitSvAvgviBciNchCZHlBKsYY2p5Vq3Qscib8ojMq/aRkOO17PNZdZ5/slcKqmCMMZ62XSl83g0AQRBsN8asRmRwfAYi3+r9j/CXtMoAVgdBsAPCR/aFdGcur2fHK4bP2f18c2NMvGelIbXzw+Nw+4+FiOg9zgTwS84Xwm+8m4fvm1Tge1y4GIvIksfJiIjotx8kV3WePwwi9Zcb54fPlXPECm2dF9ZfCL5CZBTXwBhzhuf1W8PnD47eLhUejDHFETH9ORsRV78/hyuEEOE3G1+ExVs9KToWByEIAuN7ICJuBYCkHPHt4Taq83wSBMFiRIStCYjMZXe5NHzOufRc9lr4vjrPXpFIdZ472Usqnp3L6+eEz6kAEATBSgC/InKMrvPkq50fBvnoPw7W/q9HZCnGz8N19YUHY8wQAF0R+Xb5yiAINuexier8MAmC4NKDXF9XhWk1wtjMHJsW3jo/1s5oR+qBiBAzQGRwUCpHvE8Yn3es9/FEfCAitnw3rMO5AEpGsc0VYf5vABrliJ+PiInHDgAVj/VnO5EeiCyTdjCnYtV5/uu4a1iH3wConCN+Fv5wQr81R7wJgMywflvliDcKj0MmgCbH+nMdrw9EvnELwkc357VWiPwaEwC4Ike8cxhLBlA1R/zmMJ4CIP5Yf7bj7YG8nYoPuf9A5JebHeF2N+eIV0XEYT0AcPmx/uzHcZ1n35tsyFnnebyn6jwfdX6Q7VKRu1Nxoa1zE36QQkfoEvclIt/ubUBkLfG6Yfl3RC7Yy4/ZDp6gGGN64o9l0N5D7j/v9wtyCHWMMS8hsrxXGiK6g2IArkTkV6rbgyD45xHb6UKIMaYeIt9gJwVB0DSXHNV5Pgjn8k5D5Nv9rYisAV4awAWI1OXEIAi6ONv0RmRZ0kxE6nw/gKsQ+Ra7TxAELx61D3ACYowZhj+0SEsQ+Un+JERuROMAvBxEBMbZ+XGIrPh0EyKDtM8R+Xn/EkR+tr88CIL/rd0eqxhjroO9HPR5+GOwm80zQRB8mGObQ+4/jDG3IKL1MADmIDKguAKRaY+jgiDo6W5TWDmUOjfGtETk10YD4P/whzOxyytBELjTEVXnIYfTznN5n1RE7hdrBEHgmsEV3jo/1iOSI/lA5CL8NIDliFwcNgKYDKD2sd63E/UBYBD++BbvYI96nm3vAfAdIuv0bkdkdaILj/VnOhEfyOMXAtV5gdVzHCJmZD+EdbgbkV8d7z7INjcg8uvZrvAxD8CNx/qznCgPRG7uP0bkIpvtev4FgA655BdB5NvVnwGkh9v9E8Cpx/qzHC+PsB/Iq8++J5ftDqn/QMTl+yNEBmh7wu07Hus6OJ7rHJEpiNFcV+kYqc4Pr87zeJ9U5PILQWGu80L7C4EQQgghhBAibwqrqFgIIYQQQggRBRoQCCGEEEIIEcNoQCCEEEIIIUQMowGBEEIIIYQQMYwGBEIIIYQQQsQwGhAIIYQQQggRw2hAIIQQQgghRAyjAYEQQgghhBAxjAYEQgghhBBCxDAaEAghhBBCCBHDaEAghBBCCCFEDKMBgRBCCCGEEDGMBgRCCCGEEELEMBoQCCGEEEIIEcNoQCCEEEIIIUQMowGBEEIIIYQQMYwGBEIIIYQQQsQw/w+7P8DifOIaIQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 7\n"
     ]
    },
    {
     "data": {
      "image/png": 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DXgZ8DbhE0nPz7JXMxVXrKHwzjyf9AvMpY8vZYt2Rx0/I46nxk3Q86b1890fEgwAR8QPggWnlcNy3wzxj5bxenPEcdRznSNJjgH8ivc/4CtLbUsY5F5fcBuM4i3NxiUTEw6QfOBPDbzFayVxctY5C8zLecybMb6bfPIe62Gwn5XHT472N9IMkJ+enL+MmxW9i3CXtAn4qr/e2I6qtleYZK+f14oznaMNx3Gb5w47/QPomlauB34n8JeljnItLbBNxnMW5uHzuzeOT83glc3HVOgpfIvXM9kh6dsf8V+Xxp+ZXJesi6WTgF/K/NwJExH7g83naqzqKTYrfp6eUeTnpa8U+FxEHDrvCNmLOsWrKnCPp2LKApMeRjqMHgOs3VnvbCEki/dgPpJfYS47jNsrt8wngZ4B/BF4TEf2uZZ2Ly2szcZyxHuficvrFPL4TVjgXj/QX25ZtAN5F+nDHl4Dji+lvytOvW3Qdj5aB9NmDFwIam35aPngD+MTYvBcz+efPD+QD/1FjZR6Vp4///PljGf5y4lmLbo+dNjD7F33nFqvieLmsmLYG/H2efsmi22tZh2lxBB4DnEf7lz1PAN6Xy94DHOc4zi1ePdKT5yB9a9xxGyjjXFyyYbNxdC4u30C62f4NYG1s+i7gD0k/uPYQcGoxb+VyceGB2IbA7gZuyI20l/Qesub/e4EfX3Qdj5YBOL+Iw7XAh/OBvT9PvwV4bEe5y/L8fcDHgc+QvkquD7xywrZemefXwL8AHwPuy+u5fNFtsRMG4OycK80QuT3LaWcvIlbAU3L+Buml1A+TnuJErtfuRbffsgybiSOp0x75InUD8FHgs0Vb3wec6TjONX4X5PYI0o3mlROGx4yVcy4u0bDZODoXl29geA/zPdIH0f+O9MrQ3jx9P/DrHeVWKhcXHohtCu4jgItJ30l8EPjfnJCnLrpuR9MAPA14L+ml0u/mRLkf+DLpFZ5HTCl7PulbkZofKLkGeP6M7Z1Jei/ofbncV4HXLboddspQnBSnDecvKlak7xS/gvRU7WDO70umHUdH47CZOAInAu8mdeTvJj3x2kfqxP8l8GOO49zjd+EG4hfAaRNi71xcgmGzcXQuLt8APAn4M9IDzr3AIdJnRG4B/popD55XKReVN2RmZmZmZjawah9mNjMzMzOzLeCOgpmZmZmZtbijYGZmZmZmLe4omJmZmZlZizsKZmZmZmbW4o6CmZmZmZm1uKNgZmZmZmYt7iiYmZmZmVmLOwpmZmZmZtbijoKZmZmZmbW4o2BmZmZmZi3uKJiZmZmZWYs7CmZmZmZm1uKOgpmZmZmZtbijYGZmZmZmLe4omJmZmZlZizsKZmZmZmbW4o6CmZmZmZm1/D87B/93gC/I3gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 8\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 9\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 10\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 11\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 12\n"
     ]
    },
    {
     "data": {
      "image/png": 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SzznplyRJknrOSb8kSZLUc076JUmSpJ5z0i9JkiT1nJN+SZIkqeec9EuSJEk956RfkiRJ6rn/Bwik3lNfkarnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 13\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 14\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 15\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 16\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 17\n"
     ]
    },
    {
     "data": {
      "image/png": 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ZZjYL+CHpWrwbKO/JN41x/LqyFfCau78J4O5vkK5frqzHYGybY0mnN79iZnc1BtLLqQB2zKQ3TnMq3vUsi/EL+SdZ5PJnx7gRh5kR0zJlMVObk67NnkK6l6ns/oFvx/jIGNeJWd3tMwh62UZofw9xv9lNpJv1HwGOc/dV+XKKdS3HkX7hPzN7rIzjZeONzPMj7TBQnLs1SB2FxiUyB1TkN9If7cGyTChxk9v3SU/QmA+c6/Eg4ZwnSY9DfHecfcirinHltolfZfaN6T7Z+dJPKFuRruXODgdH3uaZtMmRpnjX03gyzkwzKzt1/K4YvwXg7q8xeiDYP184Yj8LeNbdX89kqc0ZPZC+UZHfSN86xo2Y7Zu5HCmrELMuts8g6GUbof191NWkRzAvId2s/1qTsop154x0n1P+eDk18ufG51mZOopzTYPUUbiP1KPc1cwKBxPg5Bh/t3eLtPEzs6mklxy9n/Tmw9PiSSYF8YvJj+PjySVFqmJ8ey4/61jSI8t+FM+i3iS5u5UNpBtsAZ7MpL8WdRTvGtz9MdKNtZsz2hHLOjLG2UfiNYtZ4wlJbcc52qBdgP9z91+2XuoJq/EoyPdX5H8gxssAIhZPkLbNMSXl6+zTVdtnk9fjNqJR57g4bqwXjxw+nHQMvre9pZ+YzOzvgU+QOq9/6O4vtaiiWHfA3Y9scrx8JoptF2m3ZqoqznX1601v/RhIN4s6qdMwI5N+QaTf0+9l3JgG0k2fjdeU3w1Mb6POh6P8CmD3TPpc0gtNXge2ztXZOtKdsa9Wn83oq9U/1O949Gkb7EzzNzMr3vXi+olYzweBWZn0Axl9g/vJmfQ9gHUR0zmZ9N0j9uuAPXLzmEJ6h4AD52fSZ5AekejAOf2OxQaO8wGxnk56jGE2bw7prI0DH86kfzzSlgCzM+knRvrT5N6EWmf7bCoDrd/M3LM2gvSFacwbsklnQG+O9C/1O14bONaN7xLPZ2PdYpqKdYdxblJvGdVvZlac626Pfi9AT1c29Rjvj427HPhW5vMKYLd+L+PGNJAeP9Y4yM8HbqwYZuXqXRF13gZuBb5HepTqMHBSxbxOivwR4E7Ss+0bX9iu7Hcs+rgNdqZJR0Hxrh3XIdL18Q78hnRT7Z2kU88O/FtJnfMjb23E+FbSfSVjOgK5Oodkytwfbc7y+HwLMNTvWPQg1v+UaUcej7jfG/ufA9eWbJvGDxSvxL55Z+yrq4BDKubT8faZiAPpTMv9mcEjNtm0Y3J1etJGMNoxc9LlGN8Elmb2/2n9jt+GijXwe5HnpB8CbqwYDlOsu9+nK6azjIqOguLcxfbp9wL0fIXTKe1LgadIXwpeiD/eHfq9bBvbAHyR0QN8s2HnkrpnAT8hHZheIz0tqdBA5uocSroX4tWo9xPg7H7Hoc/bYGdadBQU79qxHSK9ZO3hWP+3SGcb/7RJneNIZ9fejOEe4I9bzGcf0iNXV5B+wV1Eevv2pH7HoIexPoF06eIKRt/m/mPg9Iryk0i/zj5O6hysIP2Ct0+L+XS8fSbaEH/rrdrksyrqbfA2AtiB9MCL50nH2KdIL8favN+x25CxJl2y2M7xsrBtBj3Wdffpkukso0lHYdDjXHewCIKIiIiIiMh6g3Qzs4iIiIiItEkdBRERERERKVBHQURERERECtRREBERERGRAnUURERERESkQB0FEREREREpUEdBREREREQK1FEQEREREZECdRRERERERKRAHQURERERESlQR0FERERERArUURARERERkQJ1FEREREREpEAdBRERERERKVBHQURERERECtRREBERERGRAnUURERERESk4P8B3IxX9byDYMcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 18\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 19\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 20\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 21\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxwAAABJCAYAAAC3rCDRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADdFJREFUeJzt3XusZdVdwPHvb4Y7zAxQHoXBWobQUqCUlqYvLbSVYIn2MSaloLU2AtpWo6bFULCaKi1UTfQPUtRgGrUMCZpqCYIVxBpxSh8igTE0oDwK6YuJBQrD8Jq5d+75+cdeh7vnzHneOZtz7pzvJ1nZ+6691j7r7vU7557fPfvsHZmJJEmSJDVh1aQHIEmSJGn/ZcIhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTFTlXBExOkRcXNEPBERz0TEHRFx/jL2c0FEZJ/yxSbGL0mSJGlPU5NwRMTZwG3Au6jGtR54C7A5Ip6MiDeP8eE+EBGvHuP+JEmSJHUxFQlHRBwOXA2sBnYChwIJPFKWhwF3RMSZy3yIp4HvANtrP0/F7y5JkiTtz6blTfdHqJKMHwHrqBKCH8/MY4BzSpsA/nEZ+74eOCIzX5GZhwN/DhwCfHKfRy1JkiSpr2lJODaV5UvL8tcy84dl/SaqTz0ADo2IDw2xv0Nr67+ZmbtrP18CPAZ8KCKOXu6AJUmSJA02LQnHqbX1hcx84UvdmTkP3FPb/tEh9ve62vrFEfH5iLgsIs7IzF3Al6lO33r3vgxakiRJUn8HTHoAEfESqu9otP2wS7MfAO0vjZ84xG6Pra1fXFu/NCK+SZVwALx+yDHe22PTicDzwPeH2Y8kSZK0QmwEnsvMH9vXHU084QAO7vj50S5tnq2tH9ple6f1fbadDryqrB/bp13dyT3qIyIOmVsz95oh9/PiSEgSgIhY/m4yR++fZRlL+3hhHLlUv8f6GC22Flm9avWe4xnwOO0xZiarVo34oV+2F8s4VksDgBH7tlotVkUZ66CuXY7BYmsRYM9jta/2cU4bGVMxv3sBgDWr50YfY4kPImhlC2Dp2E+7LnMyv1COxdzcHs/xUZ/vA9vXjtvQY2Xv8Q6y13O+3/677XvYx+3o38rW8uKgz/NkOa+5L7x+kcONp/b7zs/PA7BmzZohH2yp73Lna5jHqP/92uM4D/Mas8z57LTs+R1iHHv8XZwmvca8j6/t+/T7dsTcC7FBjDymVqv2+j1C38Gvdez52tB+nFHfTwzYbxlMtex8buzVrP+YW9li92L1N3dVBAes7kgHysMsLCyQmeuWMfq9jCXhiIjrgNeO2O28zLyDvQ/nc90eorY+N8S+2/u4CvgTqu9svBL4deBjwIayvTPZ6WW+R/2Bmdma3zW/ADw05L7UsEUWJz2EuuPLcirjY8qOFdDsmOYXez2VJ2Zi8TG/a+qOxbJNYxyPUeMxsj/Fwgya6r8xmriB8dEimd/d8zVgI93fl49sXJ9wHAecNGKf9qcQT3fUZ2dD+n9i0U07Qdmamd8r6/cCH4+II4EPjrKzzFzb84HK6VaZecqIY9QMMD7Uj/GhQYwR9WN8qJ9pio+xJByZueyb8mXmjoh4iqVTpQ7q0uyY2vrCELttJzHd9nUNSwlHa6hBSpIkSVqWaTkR+e7a+ob6hoiYozpdq31p26eG2F/7U41jumyrf0F9mH1JkiRJWqZpSThuqq133htjE7CWpeTggSH2105g3thl2zm19V5Xn5IkSZI0BtOScPw1sKOsz0XELwJExAbgT0v9IWV5dbtTRNxXyss79vdyqtOl3lH2QUTMRcSngZ+vtds81t9CkiRJ0h6mIuHIzCeAX61VXRsRNwL3U13C9mFgDbAjM6+ptTuplH/q2OVnqb58vgbYGhE3A98BPlNrc19mev8MSZIkqUHRvj7yNIiInwFuproLOFSXo03gwLI8KzNvrbVvD/67mXlcrX4LcEbH7lssJVg7gRNNOCRJkqRmTcUnHG2Z+RXgKOA2qqtRraG678ZDwFvryUbx1bLc3VH/e8AXgP+hSi6g+l13AbcCG002JEmSpOZN1ScckiRJkvYvU/UJhyRJkqT9iwmHJEmSpMaYcEiSJElqjAmHJEmSpMaYcEiSJElqjAmHJEmSpMaYcCxTRKyNiMsi4oGI2BkR2yLiCxFxzKTHpvGJiDdFxO9GxPUR8UhEZETsHKLfeRFxR0Q8ExFPRMTNEXH6gD6nl3ZPlH53RMT54/ttNE4RsT4i3hcRfxMR34qIHRHxbETcHRGXRsTBffoaHzMgIi4qrx0PRsRTEbErIr4bEddExCl9+hkfMygijoiIR8vfmfsGtDVGZkBEbCnx0Ku8q0e/6YuPzLSMWIC1wDeo7n6+Dfh74L/Kz48Cx096jJaxzfUNZV7rZeeAPleUds+V/rdQ3chyN3B2jz5nl+0tYAtwHfBk2c8Vkz4Olq5z9pFaTNwD/EOZ6x2l7n+BDcbH7BbgceD58vfh+lLuL/O2C3i38WGpzePmMocJ3NennTEyI6XMVZb52tylvG6lxMfED+ZKLMDlZRK+CRxcq7+o1H910mO0jG2uPwlcBmwCjmZAwgH8dGnzOHBCrf608gZjO3B4R5/DS30C76/VHw08WOrPnPSxsOw11+cBV9XnudS/DNha5u3vjI/ZLcDbgLVd6n+jzNsjwGrjwwK8s8zV5+mTcBgjs1VYSjiOG7L91MbHxA/mSivAHEtZ3xu6bL+7bHvTpMdqaWT+ByUcN5U2v91l25Vl2yc66i8p9Td06XN22fblSf/ulpHi5LR2rABrjA9Ll7lr/yF/jfEx2wVYV+LhXuCEAQmHMTJDZRkJx9TGh9/hGN3bgcOAhzLzv7tsv64sf+7FG5KmQUSspfovFSzFQV2v2NjUp89NVG9azyr718pwd1keCLwUjA/tZbEs58H4mHGfBo6n+uRroVcjY0T9THt8mHCM7vVlubXH9q0d7TQ7Xk31BvOxzPxBl+3t2Di1o/7Uju0vyMx5qu8HrAVOGtM41bxXluUC8ERZNz4EVF/opJqvB4CHS7XxMYMi4lTgE8DVmXnbgObGyOz6cERcFRF/EREfj4hju7SZ6vgw4Rhde5K7TWa9vlswaP/WNzYy81nK+ZMRcQhARLyE6hOznv0wplaiC8vylszcVdaNjxkVEZdExOaI+FJE3ANcQ3XBkV/KzFZpZnzMmIhYBfwV1bz+zhBdjJHZ9ftUn4D9FtWpUd+OiD/oaDPV8WHCMbr2pS6f67H92Y52mh2DYgP2jo96nBhT+4GIeA/wYapPN+p/EIyP2fWzwPnAucApwPepko27am2Mj9nzMeAngEsy80dDtDdGZs9twC9TnXK3nupThk9RXVHq8oi4sNZ2quPDhGN0UZY5YLtmz6DYqLfp9fMwfTSlIuJk4FqqObskM++uby5L42PGZOZZmRlUV4P5KapL426JiE/VmhkfMyQiNgJ/SHVVy83DditLY2RGZOalmXltZj6cmc9n5gOZ+cfA+0qTyyJiXVmf6vgw4Rjd02V5UI/t68vymRdhLJoug2ID9o6Pp7tsG9RHUyiqm37eQvWm8orMvLKjifEx4zJze2Z+DXgPcBfw2Yh4S9lsfMyWq4A1VKfJDMsYEQCZ+RXgTuBQ4K2leqrjw4RjdN8ry153FD+mo51mR9/YiIiDqM6V3J6ZTwNk5g7gqX79MKamXkQcCfwb1TmuVwMXd2lmfAiAzFygumFssHTFGONjtmyiOoXlL8vdpLdExBbgi2X7sbX69qksxojqHizLl5XlVMeHCcfo2qdIvLHH9nb9t16EsWi63E91Y52jyn+7O/WKjZ4xFRFzwGvLfu8f0zg1RuXLd/9CdYWQ64GPZrmAeQfjQ3WPl+VRZWl8zJ7DgDM6yk+WbetqdQeUOmNEdYeXZfuTh6mODxOO0X2DKhs8PiLe0GX7uWX5zy/ekDQNMvN54Nby47ldmvSKjZv69NlEdTm6f8/Mnfs8SI1VRBwI3Ai8GfhX4IOZuditrfGhDmeU5UNgfMyazIxuBXhFaXJ/rX576WOMCICIOAp4R/lxK6yA+GjyDon7a6H6oldSJR8H1eovKvVfm/QYLY3N/aA7jZ9V2jwOnFCrP43q5jlPAUd09Dmi1Cfw/lr9BpbuRvzOSf/ulr3mejXVJxpJdSWR9UP0MT5mpFC9GfgAcEBH/RzV1YkWqU6p2Wh8WGrzdhz97zRujMxIofpuxplAdImRr5d5u3GlxMfED+hKLFTZ3u1lErZRnYt7e22SXzXpMVrGNtfvLXN7e22OWx117+3o87nS7lngBuBmqkukLgLn9Hicc8r2FvAfwJeAJ8t+rpz0cbB0nbMLy/wkVeKxuUc50viYvQJcUObnMaqLCfwt1adg20r988AvdOlnfMxwYUDCYYzMTqm9hmwDtlB9v+fr5bUjqW7It2GlxMfED+hKLVTnV14OfJvq3Lb/K28uNk56bJaxznP7Cd+vXNCj353lCb+9vOF4+4DHehvVdwGeLP3uBH5l0sfA0nO+PjNEbCRwnPExe4Xq1Jg/Km8QtgHzVOda3wP8GX3+MWV8zG5hiITDGJmNApxMdTWzu4BHS9KwHfhPqjNq1q2k+IjyIJIkSZI0dn5pXJIkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJj/h9cVopKET6/xQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 22\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxwAAABJCAYAAAC3rCDRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADdFJREFUeJzt3XusZdVdwPHvb4Y7zAxQHoXBWobQUqCUlqYvLbSVYIn2MSaloLU2AtpWo6bFULCaKi1UTfQPUtRgGrUMCZpqCYIVxBpxSh8igTE0oDwK6YuJBQrD8Jq5d+75+cdeh7vnzHneOZtz7pzvJ1nZ+6691j7r7vU7557fPfvsHZmJJEmSJDVh1aQHIEmSJGn/ZcIhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTEmHJIkSZIaY8IhSZIkqTFTlXBExOkRcXNEPBERz0TEHRFx/jL2c0FEZJ/yxSbGL0mSJGlPU5NwRMTZwG3Au6jGtR54C7A5Ip6MiDeP8eE+EBGvHuP+JEmSJHUxFQlHRBwOXA2sBnYChwIJPFKWhwF3RMSZy3yIp4HvANtrP0/F7y5JkiTtz6blTfdHqJKMHwHrqBKCH8/MY4BzSpsA/nEZ+74eOCIzX5GZhwN/DhwCfHKfRy1JkiSpr2lJODaV5UvL8tcy84dl/SaqTz0ADo2IDw2xv0Nr67+ZmbtrP18CPAZ8KCKOXu6AJUmSJA02LQnHqbX1hcx84UvdmTkP3FPb/tEh9ve62vrFEfH5iLgsIs7IzF3Al6lO33r3vgxakiRJUn8HTHoAEfESqu9otP2wS7MfAO0vjZ84xG6Pra1fXFu/NCK+SZVwALx+yDHe22PTicDzwPeH2Y8kSZK0QmwEnsvMH9vXHU084QAO7vj50S5tnq2tH9ple6f1fbadDryqrB/bp13dyT3qIyIOmVsz95oh9/PiSEgSgIhY/m4yR++fZRlL+3hhHLlUv8f6GC22Flm9avWe4xnwOO0xZiarVo34oV+2F8s4VksDgBH7tlotVkUZ66CuXY7BYmsRYM9jta/2cU4bGVMxv3sBgDWr50YfY4kPImhlC2Dp2E+7LnMyv1COxdzcHs/xUZ/vA9vXjtvQY2Xv8Q6y13O+3/677XvYx+3o38rW8uKgz/NkOa+5L7x+kcONp/b7zs/PA7BmzZohH2yp73Lna5jHqP/92uM4D/Mas8z57LTs+R1iHHv8XZwmvca8j6/t+/T7dsTcC7FBjDymVqv2+j1C38Gvdez52tB+nFHfTwzYbxlMtex8buzVrP+YW9li92L1N3dVBAes7kgHysMsLCyQmeuWMfq9jCXhiIjrgNeO2O28zLyDvQ/nc90eorY+N8S+2/u4CvgTqu9svBL4deBjwIayvTPZ6WW+R/2Bmdma3zW/ADw05L7UsEUWJz2EuuPLcirjY8qOFdDsmOYXez2VJ2Zi8TG/a+qOxbJNYxyPUeMxsj/Fwgya6r8xmriB8dEimd/d8zVgI93fl49sXJ9wHAecNGKf9qcQT3fUZ2dD+n9i0U07Qdmamd8r6/cCH4+II4EPjrKzzFzb84HK6VaZecqIY9QMMD7Uj/GhQYwR9WN8qJ9pio+xJByZueyb8mXmjoh4iqVTpQ7q0uyY2vrCELttJzHd9nUNSwlHa6hBSpIkSVqWaTkR+e7a+ob6hoiYozpdq31p26eG2F/7U41jumyrf0F9mH1JkiRJWqZpSThuqq133htjE7CWpeTggSH2105g3thl2zm19V5Xn5IkSZI0BtOScPw1sKOsz0XELwJExAbgT0v9IWV5dbtTRNxXyss79vdyqtOl3lH2QUTMRcSngZ+vtds81t9CkiRJ0h6mIuHIzCeAX61VXRsRNwL3U13C9mFgDbAjM6+ptTuplH/q2OVnqb58vgbYGhE3A98BPlNrc19mev8MSZIkqUHRvj7yNIiInwFuproLOFSXo03gwLI8KzNvrbVvD/67mXlcrX4LcEbH7lssJVg7gRNNOCRJkqRmTcUnHG2Z+RXgKOA2qqtRraG678ZDwFvryUbx1bLc3VH/e8AXgP+hSi6g+l13AbcCG002JEmSpOZN1ScckiRJkvYvU/UJhyRJkqT9iwmHJEmSpMaYcEiSJElqjAmHJEmSpMaYcEiSJElqjAmHJEmSpMaYcCxTRKyNiMsi4oGI2BkR2yLiCxFxzKTHpvGJiDdFxO9GxPUR8UhEZETsHKLfeRFxR0Q8ExFPRMTNEXH6gD6nl3ZPlH53RMT54/ttNE4RsT4i3hcRfxMR34qIHRHxbETcHRGXRsTBffoaHzMgIi4qrx0PRsRTEbErIr4bEddExCl9+hkfMygijoiIR8vfmfsGtDVGZkBEbCnx0Ku8q0e/6YuPzLSMWIC1wDeo7n6+Dfh74L/Kz48Cx096jJaxzfUNZV7rZeeAPleUds+V/rdQ3chyN3B2jz5nl+0tYAtwHfBk2c8Vkz4Olq5z9pFaTNwD/EOZ6x2l7n+BDcbH7BbgceD58vfh+lLuL/O2C3i38WGpzePmMocJ3NennTEyI6XMVZb52tylvG6lxMfED+ZKLMDlZRK+CRxcq7+o1H910mO0jG2uPwlcBmwCjmZAwgH8dGnzOHBCrf608gZjO3B4R5/DS30C76/VHw08WOrPnPSxsOw11+cBV9XnudS/DNha5u3vjI/ZLcDbgLVd6n+jzNsjwGrjwwK8s8zV5+mTcBgjs1VYSjiOG7L91MbHxA/mSivAHEtZ3xu6bL+7bHvTpMdqaWT+ByUcN5U2v91l25Vl2yc66i8p9Td06XN22fblSf/ulpHi5LR2rABrjA9Ll7lr/yF/jfEx2wVYV+LhXuCEAQmHMTJDZRkJx9TGh9/hGN3bgcOAhzLzv7tsv64sf+7FG5KmQUSspfovFSzFQV2v2NjUp89NVG9azyr718pwd1keCLwUjA/tZbEs58H4mHGfBo6n+uRroVcjY0T9THt8mHCM7vVlubXH9q0d7TQ7Xk31BvOxzPxBl+3t2Di1o/7Uju0vyMx5qu8HrAVOGtM41bxXluUC8ERZNz4EVF/opJqvB4CHS7XxMYMi4lTgE8DVmXnbgObGyOz6cERcFRF/EREfj4hju7SZ6vgw4Rhde5K7TWa9vlswaP/WNzYy81nK+ZMRcQhARLyE6hOznv0wplaiC8vylszcVdaNjxkVEZdExOaI+FJE3ANcQ3XBkV/KzFZpZnzMmIhYBfwV1bz+zhBdjJHZ9ftUn4D9FtWpUd+OiD/oaDPV8WHCMbr2pS6f67H92Y52mh2DYgP2jo96nBhT+4GIeA/wYapPN+p/EIyP2fWzwPnAucApwPepko27am2Mj9nzMeAngEsy80dDtDdGZs9twC9TnXK3nupThk9RXVHq8oi4sNZ2quPDhGN0UZY5YLtmz6DYqLfp9fMwfTSlIuJk4FqqObskM++uby5L42PGZOZZmRlUV4P5KapL426JiE/VmhkfMyQiNgJ/SHVVy83DditLY2RGZOalmXltZj6cmc9n5gOZ+cfA+0qTyyJiXVmf6vgw4Rjd02V5UI/t68vymRdhLJoug2ID9o6Pp7tsG9RHUyiqm37eQvWm8orMvLKjifEx4zJze2Z+DXgPcBfw2Yh4S9lsfMyWq4A1VKfJDMsYEQCZ+RXgTuBQ4K2leqrjw4RjdN8ry153FD+mo51mR9/YiIiDqM6V3J6ZTwNk5g7gqX79MKamXkQcCfwb1TmuVwMXd2lmfAiAzFygumFssHTFGONjtmyiOoXlL8vdpLdExBbgi2X7sbX69qksxojqHizLl5XlVMeHCcfo2qdIvLHH9nb9t16EsWi63E91Y52jyn+7O/WKjZ4xFRFzwGvLfu8f0zg1RuXLd/9CdYWQ64GPZrmAeQfjQ3WPl+VRZWl8zJ7DgDM6yk+WbetqdQeUOmNEdYeXZfuTh6mODxOO0X2DKhs8PiLe0GX7uWX5zy/ekDQNMvN54Nby47ldmvSKjZv69NlEdTm6f8/Mnfs8SI1VRBwI3Ai8GfhX4IOZuditrfGhDmeU5UNgfMyazIxuBXhFaXJ/rX576WOMCICIOAp4R/lxK6yA+GjyDon7a6H6oldSJR8H1eovKvVfm/QYLY3N/aA7jZ9V2jwOnFCrP43q5jlPAUd09Dmi1Cfw/lr9BpbuRvzOSf/ulr3mejXVJxpJdSWR9UP0MT5mpFC9GfgAcEBH/RzV1YkWqU6p2Wh8WGrzdhz97zRujMxIofpuxplAdImRr5d5u3GlxMfED+hKLFTZ3u1lErZRnYt7e22SXzXpMVrGNtfvLXN7e22OWx117+3o87nS7lngBuBmqkukLgLn9Hicc8r2FvAfwJeAJ8t+rpz0cbB0nbMLy/wkVeKxuUc50viYvQJcUObnMaqLCfwt1adg20r988AvdOlnfMxwYUDCYYzMTqm9hmwDtlB9v+fr5bUjqW7It2GlxMfED+hKLVTnV14OfJvq3Lb/K28uNk56bJaxznP7Cd+vXNCj353lCb+9vOF4+4DHehvVdwGeLP3uBH5l0sfA0nO+PjNEbCRwnPExe4Xq1Jg/Km8QtgHzVOda3wP8GX3+MWV8zG5hiITDGJmNApxMdTWzu4BHS9KwHfhPqjNq1q2k+IjyIJIkSZI0dn5pXJIkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJjTDgkSZIkNcaEQ5IkSVJj/h9cVopKET6/xQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 23\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying activation map 24\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from read_activations import get_activations, display_activations\n",
    "v_index= 4\n",
    "x_valid = X_train[:5]\n",
    "a = get_activations(my_model, x_valid[v_index:v_index+1], print_shape_only=True)\n",
    "display_activations(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
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